Methods and systems for digitally counting features on arrays

ABSTRACT

Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

CROSS-REFERENCE

The present application is a continuation of U.S. application Ser. No. 14/508,911, filed Oct. 7, 2014, which claims the benefit of U.S. Provisional Application No. 61/887,853, filed Oct. 7, 2013, the content of the priority applications is incorporated herein by reference in its entirety.

REFERENCE TO SEQUENCE LISTING

The present application is being filed along with a Sequence Listing in electronic format. The Sequence Listing is provided as a file entitled Sequence_Listing_BDCRI_007C1.txt, created Dec. 12, 2016, which is 255,871 bytes in size. The information in the electronic format of the Sequence Listing is incorporated herein by reference in its entirety.

BACKGROUND

Array technologies have been widely used in biomedical studies for the detection of biomolecules and profiling of gene expression levels, etc. Arrays are typically comprised of immobilized probes which can bind to or hybridize with target molecules in a sample. Detection of binding or hybridization events is often achieved through the use of optical labels (e.g. fluorophores) and scanning or imaging techniques (e.g. fluorescence scanning or imaging). A feature on an array is a small region of immobilized probes that are specific for a given target molecule, e.g. probes that hybridize to specific DNA or RNA sequences. Identifying the pattern of labeled features on a hybridized array thus provides information about specific molecules, e.g. DNA or RNA molecules in the sample, which in turn can provide valuable data in biomedical studies. Two important engineering requirements for providing high quality, quantitative data for biomedical investigations are (i) to correctly image the hybridized arrays, and (ii) to correctly analyze the images to extract quantitative data. Existing optical imaging systems typically image one region of an array at a time, which can be a slow process if a number of different regions need to be imaged. In addition, current methods of image analysis typically determine a signal intensity level (i.e. an analog quantity) for each array feature. Intensity level measurements are often subject to a variety of instrumental drift and analysis errors, therefore improved methods for determining whether or not target molecules are bound to a given array feature, and improved methods for transforming that data into quantitative measures of the number of target molecules present in a sample, are of great importance to expanding the use of array technologies in biomedical applications.

SUMMARY

The methods, systems, and platforms of the present disclosure provide means for digital counting of labeled features on arrays, and thereby enable quantitative determination of the number of target molecules present in a sample through the use of stochastic labeling techniques.

Disclosed herein is an imaging platform comprising: (a) an optical instrument configured to generate an image of one or more regions of an array, wherein the array comprises a plurality of features, and wherein the plurality of features comprise a set of oligonucleotide probes, and wherein the oligonucleotide probes are complementary to a set of labels; and (b) a processor configured to perform image analysis, wherein the image analysis comprises: (i) reading the image generated by the optical instrument; (ii) locating the features of the array within the image; (iii) measuring a signal intensity for each feature; (iv) measuring a local background intensity for each feature; (v) calculating a local background corrected signal intensity for each feature using the signal intensity and local background intensities; (vi) analyzing the local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold for discriminating between labeled and non-labeled features; and (vii) calculating a number of target molecules present in a sample based on the number of labeled and non-labeled features detected and the predictions of the Poisson distribution. In some embodiments, the image generated by the optical instrument is a fluorescence image. In some embodiments, the image generated by the optical instrument is a phosphorescence image. In some embodiments, the image generated by the optical instrument is a transmitted light, reflected light, or scattered light image. In some embodiments, the image analysis further comprises reading an image that has been previously acquired and stored in a memory device. In some embodiments, locating the features of the array within the image comprises identifying predefined fiducial features on the array. In some embodiments, the calculation of a local background corrected signal intensity is performed by (i) centering a predefined analysis window on each feature within the image, (ii) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within the feature, and (iii) utilizing the signal and background intensity value statistics to calculate a local background corrected signal intensity for each feature. In some embodiments, the intensity value statistic used for calculating a local background corrected signal intensity for each feature is selected from the list including, but not limited to, the mean, the median, or the ratio of signal to background intensities. In some embodiments, the analyzing of local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold comprises performing one or more statistical analyses selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis. In some embodiments, the analyzing of local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold comprises fitting a model function to the intensity data by varying model parameters. In some embodiments, the analyzing of local background corrected signal intensities for the complete set of features to determine a dynamic signal intensity threshold comprises maximizing a quality metric relating to a statistical difference between intensities above the threshold and below the threshold.

In some embodiments, an array reader system comprising an output unit for calculating an absolute number of target molecules in a sample is described, wherein the array reader system is configured to read an array comprising a plurality of labeled and non-labeled features. In some embodiments, the array reader system may further comprise an optical imaging system. In some embodiments, the calculation of absolute number of target molecules in a sample is based on transforming optical image data produced by the optical imaging system into a count of the number of labeled and non-labeled features on an array. In some embodiments, the output unit comprises a digital processor and executable software, wherein the executable software comprises computer code for transforming optical image data into a count of the number of labeled and non-labeled features. In some embodiments, the array comprises a microarray, microscope slide, or microwell plate.

In some embodiments of the disclosed array reader system, the optical imaging system has a magnification of less than 1, equal to 1, or greater than 1. In some embodiments, the optical imaging system comprises a fluorescence imaging system. In some embodiments, the optical imaging system comprises a phosphorescence imaging system. In some embodiments, the optical imaging system comprises an imaging system that operates in a transmitted light, reflected light, or scattered light imaging mode, or combinations thereof. In some embodiments, the optical imaging system comprises one or more image sensors, wherein the one or more image sensors have a resolution of at least 320×240 pixels. In some embodiments, the one or more image sensors comprise CCD image sensors. In some embodiments the one or more image sensors comprise CMOS image sensors. In some embodiments, the one or more image sensors comprise one or more circuit boards. In some embodiments, the optical imaging system further comprises one or more components selected from the group including, but not limited to, a microscope objective, a camera lens, a finite-conjugate lens, an infinite-conjugate lens, a plano-convex lens, a double convex lens, a plano-concave lens, a double concave lens, an achromatic cemented doublet, or a bandpass filter. In some embodiments, the optical imaging system comprises a fluorescence imaging system that is designed for use with fluorescein, Cy3, Cy5, or phycoerythrin fluorophores. In some embodiments, the optical imaging system further comprises an illumination system including at least one light source, wherein the at least one light source is an LED or LED assembly. In some embodiments, the at least one light source is electronically synchronized with the image sensor, the at least one light source being turned on when the image sensor is acquiring an image and turned off when the image sensor is not acquiring an image.

In some embodiments of the disclosed array reader system, the illumination system is an off-axis illumination system that satisfies the Scheimpflug condition. In some embodiments, the illumination system is an off-axis illumination system does not satisfy the Scheimpflug condition. In some embodiments, the illumination system is an off-axis illumination subsystem comprising a Kohler illumination system. In some embodiments, the illumination system is an off-axis illumination system comprising an Abbe illumination system. In some embodiments, the illumination system is an epi-illumination system comprising a Kohler illumination system. In some embodiments, the illumination system is an epi-illumination system comprising an Abbe illumination system. In some embodiments, the illumination system is a trans-illumination system comprising a Kohler illumination system. In some embodiments, the illumination system is a trans-illumination system comprising an Abbe illumination system.

In some embodiments of the disclosed array reader system, the optical imaging system further comprises a translation stage, wherein the translation stage is a single-axis translation stage, a dual-axis translation stage, or a multi-axis translation stage.

In some embodiments of the disclosed array reader system, the optical imaging system and output unit are combined within a single, stand-alone instrument. In some embodiments, the optical imaging system and output unit are configured as separate instrument modules.

In some embodiments of the disclosed array reader system, executable software automatically locates features of the array within the acquired image. In some embodiments, the executable software also performs local background correction by (i) centering a predefined analysis window on each array feature within an image, (ii) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within the feature, and (iii) utilizing the signal and background intensity value statistics to calculate a background corrected signal intensity value for each feature.

In some embodiments of the disclosed array reader system, executable software performs a k-means clustering analysis of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the executable software also performs a k-medoids clustering analysis of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array.

In some embodiments, executable software performs a mixture model statistical analysis of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, executable software also performs an empirical analysis based on sorting of background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments executable software performs an empirical analysis based on sorting of pairwise differences in background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, an executable software module performs one or more statistical analyses of the background corrected signal intensity values for the complete set of array features, thereby determining a dynamic signal intensity threshold for discrimination between labeled and non-labeled features of the array, and wherein the one or more statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis.

In some embodiments of the disclosed array reader system, executable software calculates the absolute number of target molecules in a sample based on the number of labeled and non-labeled features detected and the predictions of the Poisson distribution. In some embodiments, executable software also calculates a confidence interval for the number of target molecules.

Also disclosed herein is a digital imaging platform comprising: (a) an optical instrument configured to generate an image of one or more regions of an array, wherein the array comprises a plurality of features comprising oligonucleotide probes, and wherein the oligonucleotide probes are complementary to a set of labels; and (b) a digital processor, wherein the digital processor is configured to perform image analysis comprising: (i) transforming background corrected signal intensities for a plurality of features to produce binary output data that determines the number of labeled and non-labeled features in the one or more regions of the array; and (ii) calculating a number of target molecules present in a sample based on the number of labeled and non-labeled features detected within the one or more regions of the array. In some embodiments, the image analysis further comprises automatically locating the features of the array within the image. In some embodiments, the image analysis further comprises correcting a signal intensity for each feature for a local background intensity. In some embodiments, the image analysis further comprises performing one or more statistical analyses of the corrected signal intensities for a plurality of features to define one or more dynamic signal intensity thresholds for the one or more regions of the array, where the statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis. In some embodiments, the calculation of the number of target molecules present in a sample is based on both the number of labeled and non-labeled features detected within the one or more regions of the array and on the predictions of the Poisson distribution.

Also disclosed herein is a non-transitory computer readable medium storing a program that calculates a number of labeled features on an array, wherein the array comprises a plurality of feature sets, and wherein individual features of a feature set comprise a set of oligonucleotide probes that are capable of hybridizing to a set of labels, the non-transitory computer readable medium comprising: (a) computer code that locates individual features of the array within a digital image of the array; (b) computer code that performs a local background correction of a signal intensity for one or more features; (c) computer code that analyzes the corrected signal intensity data for the complete set of features and determines a corrected signal intensity threshold; and (d) computer code that transforms the corrected signal intensity for the features into binary output data, thereby providing a count of the number of labeled features on the array. In some embodiments, the computer code for locating individual features of the array within the digital image comprises identifying predefined fiducial features on the array. In some embodiments, the computer code for performing a local background correction of signal intensity for each feature comprises a calculation utilizing a statistic for signal and background intensities selected from the list including, but not limited to, the mean, the median, or the ratio of signal to background intensities. In some embodiments, the computer code for analyzing corrected signal intensities for the complete set of features to determine a corrected signal intensity threshold comprises performing one or more statistical analyses selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis.

Also disclosed herein is a computer implemented method for performing local background correction of array signal intensity data, the method comprising: (a) centering a predefined data analysis window on a feature within a digital image of the array; (b) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within or around the array feature; and (c) utilizing the signal and background intensity value statistics to calculate a background corrected signal intensity for the array feature. In some embodiments, the computer implemented method further comprises automatically locating the array feature using, e.g., a predefined set of fiducial features on the array. In some embodiments, the intensity value statistic used for calculation of a background corrected signal intensity is selected from the list including, but not limited to, the mean, the median, or the ratio of signal to background intensities.

Disclosed herein is a computer implemented method for determining a dynamic image intensity threshold for use in discriminating between labeled and non-labeled features on an array comprising a plurality of labeled and non-labeled features, the computer implemented method comprising: (a) measuring image intensity data for each feature of the array; (b) performing a local background correction on the image intensity data for each feature on the array; and (c) performing one or more statistical analyses of the background corrected image intensity data for the complete set of array features, thereby determining a dynamic image intensity threshold for discrimination between labeled and non-labeled features of the array, and wherein the one or more statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or an empirical analysis.

Also disclosed is a mechanism comprising: (a) a closure; (b) a housing which magnetically holds the closure in a first position; and (c) a translation stage which magnetically holds the closure in a second position. In some embodiments, the mechanism further comprising a gasket positioned between the closure and the housing. In some embodiments, the gasket is attached to the closure. In some embodiments, the gasket is attached to the housing. In some embodiments, the closure and housing are substantially opaque, and the gasket creates a substantially light-tight seal between the closure and the housing in the first position. In some embodiments, one or more magnets are positioned to hold the closure onto the housing in the first position. In some embodiments, one or more magnets are positioned to hold the closure onto a first surface of the translation stage in the second position. In some embodiments, two or more pairs of mating locating features to align the closure with the translation stage in the second position. In some embodiments, two or more pairs of mating locating features to align the closure with the housing in the first position. In some embodiments, the pairs of mating locating features comprise conical pins and conical holes. In some embodiments, the housing comprises an optical instrument. In some embodiments, the translation stage includes a sample holder. In some embodiments, the sample holder is designed to hold a microscope slide, a microarray, or a microwell plate. In some embodiments, the closure is not hinged. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of fasteners such as screws or clips. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of an adhesive. In some embodiments, the closure does not use a latch or mechanical lock.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

FIGS. 1A-1G show one example of an optical system, and components thereof. FIG. 1A depicts an isometric projection of the exemplary optical system. FIG. 1B depicts a top view of the optical system. FIG. 1C depicts a dimetric view of the optical system. FIG. 1D depicts a front view of the optical system. FIG. 1E depicts a side view of the exemplary optical system comprising a single axis stage, an imaging system, and an illumination system. FIG. 1F depicts a back view of the optical system. FIG. 1G depicts components that control the operation of the optical system.

FIG. 2 shows an exemplary layout of lenses in an imaging system.

FIG. 3 shows an exemplary layout of lenses in an illumination system.

FIG. 4A shows an array image acquired from the optical instrument.

FIG. 4B shows a histogram of intensities for individual features.

FIG. 5 shows a feature intensity distribution observed for hybridization of array probes with labeled target molecules in atitration experiment.

FIG. 6A shows a noisy array image. FIG. 6B shows the intensity distribution before background adjustment. FIG. 6C shows the intensity distribution after background adjustment.

FIGS. 7A-7D show external views of instrument designed for digital counting of features on arrays.

FIG. 8 shows an internal view (front view; 3D CAD model) of an instrument designed for digital counting of features on arrays.

FIG. 9 depicts an internal view (rear view; 3D CAD model) of an instrument designed for digital counting of features on arrays.

FIG. 10 shows a photograph of a system with the sample loading stage in the extended (loading) position, having pulled the door away from the front panel. A Pixel16 array assembly is shown in the loading tray.

FIG. 11A shows an exploded view of a door assembly that utilizes a magnetic mechanism for positioning a door on a sample compartment stage. FIG. 11B shows another exploded view of the door assembly that illustrates conical locator features for ensuring proper alignment of the door with the stage.

FIG. 12 depicts an exploded view of an upper stage assembly with magnets which mate with a corresponding pair of magnets on the door.

FIG. 13 shows an exploded view of a front panel assembly with magnets which mate with a corresponding pair of magnets on the door.

FIG. 14 shows the viewing reference orientation for array production and analysis in one embodiment of an array, showing the 16 array locations on a glass substrate. Nominal dimensions are shown (in millimeters).

FIG. 15 shows the layout of features on one embodiment of an array. Nominal dimensions are shown (in millimeters).

FIG. 16 shows the layout of an array designed for digital counting of target molecules in a sample, including the positions of positive controls (fiducials), negative controls, and index spots.

FIG. 17A shows an example of an array image after transformation to the reference orientation. FIG. 17B the image size (in pixels) and a schematic of feature positions for the two-array image.

FIGS. 18A-B depict software workflows for performing an experiment on an instrument designed for digital counting of features on arrays. (A) Workflow for a single-axis system with manual sample loading, and (B) workflow for a dual-axis system with automatic sample tray loading.

FIG. 19 depicts an analysis window comprising a 12×12 pixel area associated with each feature in the array.

FIG. 20 depicts a map of the pixel designations within the analysis window for each feature in the array.

FIG. 21 depicts a scatter plot (upper) of intensity data obtained from an image of an array that illustrates the different categories of features identified by the analysis software, and a histogram (lower) of the feature intensity data. Dashed lines indicate examples of intensity thresholds determined by the software that are used to discriminate between labeled (“on”) and non-labeled (“off”) features.

FIG. 22 depicts a scatter plot (upper) and histogram (middle) of array feature intensity data that illustrate the use of an intensity threshold (dashed lines) that discriminate between labeled (“on”) and non-labeled (“off”) features of an array. In one embodiment of the presently described analysis methods, the threshold is determined from the maximum slope of a plot of sorted intensity data (lower).

FIG. 23 depicts the results of fitting a 3-component distribution model used to determine an intensity threshold in one embodiment to a 128-bin feature intensity histogram.

FIG. 24A illustrates the deviance calculations for fitting one normal distribution to histograms of array feature intensity data. FIG. 24B illustrates the deviance calculations for fitting two normal distributions to histograms of array feature intensity data. In some embodiments, deviance measurement may be used as a quality metric.

FIG. 25 depicts the uncertainties calculated for various methods of combining output data from replicate experiments.

FIG. 26 shows dilution series data for using digital counting of labeled features on an array to measure the number of target RNA molecules in a sample.

FIG. 27 shows a screenshot of the output data provided by the system software for a dilution series experiment. For each array used in the dilution series experiment, the software displays a histogram of feature intensity data with a blue line indicating the value of the threshold used for counting, overlaid on a digital representation of the array.

DETAILED DESCRIPTION OF THE INVENTION

Array technologies have been widely used in biomedical studies for the detection of biomolecules and profiling of gene expression levels, etc. Arrays are typically comprised of immobilized probes which can bind to or hybridize with target molecules in a sample. Detection of binding or hybridization events is often achieved through the use of optical labels (e.g. fluorophores) and scanning or imaging techniques (e.g. fluorescence scanning or imaging). A feature on an array is a small region of immobilized probes that are specific for a given target molecule, e.g. probes that hybridize to specific DNA or RNA sequences. Identifying the pattern of labeled features on a hybridized array thus provides information about the presence of specific molecules, e.g. DNA or RNA molecules in the sample, which in turn can provide valuable data in biomedical studies. Two important engineering requirements for providing high quality, quantitative data for biomedical investigations are (i) to correctly image the hybridized arrays, and (ii) to correctly analyze the images to extract quantitative data. Existing optical imaging systems typically image one region of an array at a time, which can be a slow process if a number of different regions need to be imaged. In addition, current methods of image analysis typically determine an analog signal intensity level (i.e. a signal that can have any value between some minimum and maximum values that are determined by various instrumental and experimental parameters) for each array feature. Analog intensity level measurements are often subject to a variety of instrumental drift and analysis errors, therefore improved methods for determining whether or not target molecules are bound to a given array feature, and improved methods for transforming that data into quantitative measures of the number of target molecules present in a sample, are of great importance to expanding the use of array technologies in biomedical applications.

The advantages of the methods, systems, and platforms disclosed herein include: (i) simultaneous imaging of multiple regions of an array for higher throughput image acquisition, and (ii) improved methods for reduction of image data to a digital determination of the presence or absence of bound target molecules (or target molecule labels) for each feature of an array, thereby providing for improved quantitation in some types of array experiments, for example, those utilizing a set of stochastic labels for quantifying the number of target molecules present in a sample. The use of stochastic labeling techniques is described in U.S. Pat. No. 8,835,358 and PCT application US2011/065291, which are incorporated in their entirety herein by reference. In addition to providing a means for more quantitative detection of target molecules, the use of stochastic labeling techniques allows for mitigation of amplification bias in assays involving nucleic acid amplification.

Accordingly, disclosed herein are methods, devices, systems, and platforms for digital counting of labeled features on arrays comprising: (i) optical instruments configured to form images of one or more regions of an array, (ii) arrays comprising a plurality of features further comprising a plurality of probes, and wherein one or more regions of an array may comprise one or more sub-arrays, and wherein the arrays or sub-arrays are designed for use with sets of stochastic labels, and (iii) computer implemented methods for receiving input image data; locating array features within array images; correcting the signal intensity values associated with each feature for local background intensity values; determining dynamic signal intensity thresholds for the one or more array regions by performing statistical analyses of the corrected signal intensity data for a plurality of features; counting the number of labeled and non-labeled features on the one or more regions of the array by comparing corrected signal intensity data for the features to signal intensity thresholds; and calculating the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.

In some embodiments, systems are described which comprise: (i) an optical instrument (or reader) configured to form images of one or more regions of an array, (ii) a digital processor configured to perform executable instructions and store data in memory devices, and (iii) computer code for performing image analysis in order to transform image data into a digital count of the number of labeled and non-labeled features on the one or more regions of the array. In some embodiments, the computer code further comprises performing a calculation of the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.

In some embodiments, platforms are described which comprise: (i) arrays designed for use in stochastic labeling experiments, wherein the arrays comprise a plurality of features further comprising a plurality of probes, and wherein one or more regions of an array may comprise one or more sub-arrays, and wherein the arrays or sub-arrays are designed for use with sets of stochastic labels, (ii) an optical instrument (or reader) configured to form images of one or more regions of an array, (iii) a digital processor configured to perform executable instructions and store data in memory devices, and (iv) computer code for performing image analysis in order to transform image data into a digital count of the number of labeled and non-labeled features on the one or more regions of the array. In some embodiments, the computer code further comprises performing a calculation of the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.

In some embodiments, software applications (or computer code products) are described that determine the number of labeled features on an array, wherein the software application includes code for performing one or more of the following computer implemented methods: (i) receiving input image data, (ii) locating array features within array images, (iii) correcting the signal intensity values associated with each feature for local background intensity values, (iv) determining dynamic signal intensity thresholds for the one or more array regions by performing statistical analyses of the corrected signal intensity data for a plurality of features, (v) counting the number of labeled and non-labeled features on the one or more regions of the array by comparing corrected signal intensity data for the features to signal intensity thresholds, and (vi) calculating the number of target molecules in a sample, for one or more target molecule species, from the number of labeled and non-labeled features detected on the one or more regions of the array.

In some embodiments, computer implemented methods are described for performing local background correction of array signal intensity data, the methods comprising: (i) centering a predefined data analysis window on each array feature within a digital image of the array, (ii) calculating mean or median intensity values for signal and background pixels according to a predefined pattern of pixels within or around each array feature, and (iii) subtracting the mean or median background intensity from the mean or median signal intensity to determine a background corrected signal intensity value for each array feature.

In some embodiments, computer implemented methods are described for determining dynamic image intensity thresholds from the corrected image intensity data for a plurality of features on an array, the methods comprising: (i) collecting image intensity data for each feature of the array, (ii) optionally performing a local background correction on the image intensity data for each feature on the array; and (iii) performing one or more statistical analyses of the background corrected image intensity data for the complete set of array features, thereby determining a dynamic image intensity threshold for discrimination between labeled and non-labeled features of the array. In some embodiments, the one or more statistical analyses are selected from the list including, but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, or empirical analyses based on sorting of image intensity values or pairwise differences in image intensity values. As used herein, the term “dynamic intensity threshold” refers to a parameter that is determined based on an analysis of data derived from the experiment in progress. The use of a dynamic image intensity threshold for discrimination between labeled and non-labeled features of an array helps to minimize or eliminate errors in data processing that may arise from instrumental drift or experimental procedure.

DEFINITIONS

Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art in the field to which this disclosure belongs. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise. Any reference to “or” herein is intended to encompass “and/or” unless otherwise stated.

As used herein, the terms “system” and “platform” are used interchangeably. Similarly, the terms “image sensor”, “imaging sensor”, “sensor chip”, and “camera” are used interchangeably to describe two dimensional photosensors used for imaging purposes, and the use of the terms “image intensity” and “signal intensity” are also used interchangeably in describing data analysis methods. Finally, unless otherwise stated, the terms “software”, “software application”, “software module”, “computer program”, and “computer code” are also used interchangeably.

Stochastic Labeling Methods

The use of stochastic labeling techniques is described in U.S. Pat. No. 8,835,358 and PCT application US2011/065291, which are incorporated in their entirety herein by reference.

Briefly, high-sensitivity single molecule digital counting may be achieved through the stochastic labeling of a collection of identical target molecules. Each copy of a target molecule is randomly labeled using a large, non-depleting reservoir of unique labels. The uniqueness of each labeled target molecule is determined by the statistics of random choice, and depends on the number of copies of identical target molecules in the collection compared to the diversity of labels. The size of the resulting set of labeled target molecules is determined by the stochastic nature of the labeling process, and analysis of the number of labels detected then allows calculation of the number of target molecules present in the original collection or sample. When the ratio of the number of copies of a target molecule present to the number of unique labels is low, the labeled target molecules are highly unique (i.e. there is a very low probability that more than one target molecule will have been labeled with a given label), and the digital counting efficiency is high. This stochastic methodology transforms the problem of counting molecules from one of locating and identifying identical molecules to a series of yes/no digital questions regarding detection of a set of predefined labels. In some embodiments, the labeled products are detected by means of DNA sequencing. In other embodiments, the labeled products for one or more target molecules of choice are detected with high specificity using the array readout systems described herein.

Arrays and Features

Disclosed herein are arrays designed for use in stochastic counting of one or more target molecules in a sample. Arrays provide a means of detecting the presence of labeled target molecules, wherein the labels comprise a large and diverse set of unique labels.

In many embodiments, arrays comprise a plurality of features (or spots) on the surface of a substrate, wherein each feature further comprises a plurality of attached probes. In some embodiments, the array may comprise one or more regions, each of which may comprise a plurality of features or sub-arrays. For example, an array may comprise 2, 3, 4, 5, 6, 7, 8, 9, 10 or more regions, or alternatively, an array may comprise 15, 20, 25, 30, 35, 40, 45, 50 or more regions. In some embodiments, an array may comprise 60, 70, 80, 90, 100 or more regions. In other embodiments, an array may comprise hundreds, thousands, or tens of thousands of regions.

Non-limiting examples of arrays include microtiter plates, microwell plates, 16-well microscope slides, spotted microarrays, or microarrays fabricated by in situ solid-phase synthesis. A region of an array may comprise one well of a 16-well microscope slide, one well of a glass-bottomed 96-well plate, or one well of a glass-bottomed 384-well plate. Alternatively, a region of an array may comprise more than one well, for example, in some embodiments, a region may comprise 2 adjacent wells, 4 adjacent wells; or a larger number of wells positioned in close proximity to each other. In some embodiments, the arrays may comprise high-density oligonucleotide arrays with more than 1,000 features per square millimeter, and a region on the array may comprise a selected area of the array substrate surface, for example, an area of approximately 1 mm×1 mm.

As indicated previously, in many embodiments, the set of probes attached to a set of features of an array are selected for detection of a specific set of unique labels designed for use in stochastic labeling studies. The attachment of the probes to the array substrate may be covalent or non-covalent, and permanent or temporary. A probe may be a sequence of monomers including, but not limited to, for example, deoxy-ribonucleotides, ribonucleotides, amino acids, or synthetic monomers, or they may be a sequence of oligomers, including, but not limited to, for example, oligonucleotides (e.g. DNA or RNA sequences) or peptide sequences. In some cases, a probe may be a macromolecule, including but not limited to, for example, antibodies or antibody fragments. Each feature on an array corresponds to a small area of the array substrate comprising immobilized probes having the same molecular sequence that bind to or hybridize with the same target molecule. Two or more features on the array may be identical, similar, or different. In many embodiments, arrays will include one or more fiducial marks used for alignment or orientation purposes, as well as positive and negative control features in addition to feature sets used for detection of a stochastic label set. Positive control features may comprise probes that bind to or hybridize with molecules known to be always present in a sample, or probes that bind to or hybridize with molecules spiked into a sample in a controlled fashion. Negative control features may comprise probes that are specific for molecules that are known to be absent from a sample, or they may comprise features having no probes attached to the substrate surface at all.

In many embodiments, the array substrate, also called a support, may be fabricated from a number of materials. The materials may be solid. The materials may be semi-solid. Examples of materials that may be used to fabricate array substrates include, but are not limited to, glass, fused silica, silicon, polymer, or paper.

In some embodiments, the present disclosure also describes arrays for use in stochastic labeling studies. In particular, arrays are described wherein the arrays comprise a plurality of features having immobilized probes thereon that are complementary to a set of labels designed for use in stochastic labeling experiments, and wherein there is at least one feature on the array for every label in the label set. Some embodiments include an array comprising: (a) a plurality of features, optionally organized into a plurality of sub-arrays, wherein the plurality of features comprise: (i) one or more fiducial features comprising oligonucleotide probes of a defined fiducial sequence; (ii) one or more positive control features comprising oligonucleotide probes of one or more defined positive control sequences; (iii) one or more negative control features having no oligonucleotide probes; and (iv) a plurality of label set features comprising oligonucleotide probes, wherein each individual feature comprises a unique sequence selected from a set of label sequences designed for stochastic labeling of one or more target molecules. In some embodiments, the arrays described in the present disclosure comprise oligonucleotide probe sequences comprising 25-mers, wherein the 5′ terminus may optionally be labeled with a 6 carbon atom amino-modifier. In some embodiments, the arrays described in the present disclosure further comprise oligonucleotide probes comprising the set of 960 unique oligonucleotide sequences listed in Table 1. In some embodiments, the arrays described in the present disclosure comprise a set of oligonucleotide probes that are 70% homologous, 80% homologous, 85% homologous, 90% homologous, or 95% homologous with the set of sequences listed in Table 1. In some embodiments, the array described in the present disclosure comprise a set of oligonucleotide probes that includes 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% or more of the sequences listed in Table 1.

Hybridization and Detection

In many embodiments of the disclosed methods, systems, and platforms, samples may be processed prior to placing them in contact with the immobilized probes on arrays. For example, target molecules in the samples may be labeled with fluorescent dye molecules and/or stochastic labels during the sample preparation step. Prior to hybridization with oligonucleotide probes, for example, target DNA or RNA molecules may be covalently linked to fluorescent dye molecules including, but not limited to, fluorescein, Cy3, or Cy5. Alternatively, target molecules may be labeled after binding or hybridizing to probes on the array. For example, target molecules may be covalently linked to biotin prior to binding or hybridization with probes on the array. Following the binding or hybridization step, the immobilized target molecules may then be labeled with streptavidin conjugated to optical tags including, but not limited to, phycoerythrin, quantum dot nanoparticles, gold nanoparticles, or blue latex beads. There are many methods for labeling target molecules, either before or after binding or hybridization to the array, and many possible choices for suitable optical labels or tags.

Once a sample has been contacted with an array, the array (or one or more regions of the array) may comprise one or more labeled features. Each region of an array that has been contacted with a sample comprising labeled target molecules (where the target molecules are labeled either before or after contact with the array) may, for example, comprise zero, one, two, or more labeled features. Alternatively, a region of an array that has been contacted with a sample may comprise 2, 3, 4, 5, 6, 7, 8, 9, 10 or more labeled features. In some embodiments, a region of an array that has been contacted with a sample may comprise 15, 20, 25, 30, 35, 40, 45, 50, or more labeled features. In high-density arrays, a region of an array that has been contacted with a sample may comprise more than 100 labeled features, more than 1,000 labeled features, more than 10,000 labeled features, more 100,000 labeled features, or more than 1,000,000 labeled features.

Optical Instruments

The methods, systems, and platforms described herein may comprise an optical instrument used for finite-conjugate digital imaging of one or more regions of an array, wherein the instrument typically includes an illumination system, an imaging system, and a translation stage. In some embodiments, the instrument operates as a “macroscope” having a magnification of less than one. In other embodiments, the instrument operates as a “microscope” having a magnification of greater than one. In still other embodiments, the instrument operates as a “contact imager” having a magnification equal to one. The choice of magnification will typically depend on the field of view required to image the region of interest, and on the size of the image sensor.

By way of non-limiting example, if a region of an array comprises a single well of a 16-well microscope slide, or a single well of a glass-bottomed 96-well plate, the dimensions of the region to be imaged may be approximately 7 mm×7 mm, and the pitch (center-to-center distance between two adjacent regions of the array may be approximately 9 mm. In some embodiments, the optical instrument may be used to take an image of one well at a time, or an image of 2 adjacent wells simultaneously, or an image of 4 (2×2) adjacent wells simultaneously, and the required field of view, or region to be imaged, may be adjusted accordingly. Similarly, the optical instrument may form an image of 6 (3×2 or 2×3), 8 (4×2 or 2×4), 9 (3×3), 10 (5×2 or 5×2), or 12 (6×2, 4×3, 3×4, or 2×6) adjacent wells simultaneously.

By way of another non-limiting example, if a region of an array is a single well of a glass-bottomed 384-well plate, the dimensions of the region to be imaged may be approximately 3 mm×3 mm, and the pitch between two adjacent regions of the array may be approximately 4.5 mm. Again, in some embodiments, the optical instrument may be used to take an image of one well at a time, or an image of 2 adjacent wells simultaneously, or an image of 4 (2×2), 6 (3×2 or 2×3), 8 (4×2 or 2×4), 12 (4×3 or 3×4), or 16 (4×4) adjacent wells simultaneously.

In another non-limiting example, the optical instrument may be used to image high-density oligonucleotide arrays, for example arrays having more than 1,000 features per square millimeter, and a region on the array may be approximately 1 mm×1 mm in area, for example.

Imaging System

One main component of the optical instrument is an imaging system. The imaging system may include one or more lenses in addition to a CCD or CMOS camera. Typically the CCD or CMOS camera will have a resolution between a few hundred thousand and a few million pixels. A high resolution camera may have tens of millions of pixels, or more.

The imaging system may be configured to magnify the image of the array. The required magnification of the imaging system can be determined by the required field of view and by the size of the CCD or CMOS sensor. By way of a non-limiting example, if the optical instrument is used to take an image of 2 adjacent wells of a 16-well microscope slide simultaneously, the required field of view is approximately 16 mm×8 mm. If the light-sensitive area of the CCD or CMOS sensor is about 4.8 mm×3.6 mm, the instrument is a macroscope and a magnification of about 0.3 is required. In this case, only data from the central 4.8 mm×2.4 mm of the sensor would be used.

By way of non-limiting example, an appropriate imaging system with a magnification of 0.3 may be constructed using an achromatic cemented doublet lens with a focal length of 85 mm and an infinite-conjugate camera lens with a focal length of 25 mm. If a spectrally selective emission filter is used (for example, a single-band interference filter, multi-band interference filter, longpass interference filter, or longpass colored glass filter), and this filter is typically located between the achromatic cemented doublet lens and the camera lens. Additional configurations of an imaging system with a magnification of 0.3 are possible. For example, the achromatic cemented doublet lens can be omitted, and a finite-conjugate camera lens can be used instead of an infinite-conjugate camera lens. In this case, the spectrally selective emission filter is preferably located on the long-conjugate side of the camera lens.

A sensor with a light-sensitive area of 4.8 mm×3.6 mm is known as a ⅓-inch format sensor. If a sensor of different size is used, the required magnification will be different. By way of a non-limiting example, if the required field of view is 16 mm×8 mm and a sensor having a light-sensitive area of 6.4 mm×4.8 mm (known as a ½-inch format sensor) is used, then the required magnification is 0.4. An appropriate imaging system with a magnification of 0.4 can be constructed using, for example, an achromatic cemented doublet lens with a focal length of 85 mm and an infinite-conjugate camera lens with a focal length of 35 mm.

As another non-limiting example, if the dimensions of a region are about 0.66 mm×0.66 mm and a sensor with a light-sensitive area of 8.8 mm×6.6 mm (known as a ⅔-inch format sensor) is used, then the instrument is a microscope and the required magnification is about 10. In this case, only data from the central 6.6 mm×6.6 mm of the sensor will be used. An appropriate imaging system with a magnification of 10 can be constructed using, for example, an infinite-conjugate microscope objective with a focal length of 20 mm and a microscope tube lens with a focal length of 200 mm, with a spectrally selective emission filter typically located between the microscope objective and the tube lens. Alternatively a finite-conjugate 10× microscope objective can be used and the microscope tube lens can be omitted. In this case the spectrally selective emission filter can be located on the long-conjugate side of the microscope objective.

An imaging system of any required magnification can be constructed using a combination of off-the-shelf and custom optical elements that does not necessarily include either a camera lens or a microscope objective. The optical elements may have various combinations of spherical, flat, aspheric, or diffractive surfaces.

Illumination System

Another main component of the optical instrument is an illumination system. The purpose of the illumination system is to illuminate the array within the field of view of the CCD or CMOS camera. To reduce sensitivity to edge effects and to misalignment, it may be desirable for the illuminated area to be slightly larger than the camera's field of view. By way of a non-limiting example, if the field of view is about 16 mm×8 mm, a reasonable illuminated area may be about 18 mm×10 mm. The types of illumination may be Abbe, Kohler, or neither Abbe nor Kohler illumination. Abbe illumination and Kohler illumination are well known and are described in, for example, Chapter 14 of Optical System Design, Second Edition by Robert E. Fischer et al., SPIE Press, McGraw-Hill, NY, 2008.

In some embodiments, the illumination system may be used for off-axis illumination. In other embodiments, the illumination system may be used for trans-illumination or epi-illumination. If the illumination system is used for off-axis illumination or trans-illumination, then the illumination system and the imaging system are separate from each other, with no shared optical components. If the illumination system is used for epi-illumination, then the illumination system and the imaging system may share a beamsplitter and possibly one or more lenses. The beamsplitter may be a plate beamsplitter or a cube beamsplitter. If the optical instrument is used for fluorescence imaging, the beamsplitter is typically a single-edge or multi-edge longpass dichroic beamsplitter.

Often the illumination system may contain a square or rectangular aperture so that the illuminated area has the same shape as the region that is imaged by the CCD or CMOS camera. In embodiments where off-axis illumination is used, the aperture may be trapezoidal in shape instead of square or rectangular. An off-axis illumination system may or may not satisfy the Scheimpflug condition. The Scheimpflug condition is described in, for example, Modern Optical Engineering, Second Edition by Warren J. Smith, McGraw-Hill, NY, 1990.

In some embodiments, the illumination system may contain one or more of the following: spherical lenses, aspheric lenses, a solid homogenizing rod with a rectangular or trapezoidal cross section, a hollow homogenizing light tunnel with a rectangular or trapezoidal cross section, a microlens array or a pair of microlens arrays, a stationary or rotating diffuser, a compound parabolic concentrator, a non-imaging optical element other than a compound parabolic concentrator (e.g., a free-form catadioptric element), an optical fiber, a fiber bundle, or a liquid light guide.

The illumination system may contain one or more light sources, selected from the group including, but not limited to, one or more LEDs, one or more lasers, a xenon arc lamp, a metal halide lamp, or an incandescent lamp, or a combination thereof. The illumination system may also contain a spectrally selective excitation filter selected from the list including, but not limited to, a single-band interference filter, a multi-band interference filter, or a shortpass interference filter. If the illumination system contains two or more light sources, they may be the same (by way of non-limiting example, two or more LEDs with peak emission wavelengths of about 525 nm for excitation of Cy3 dye, mounted as close together as possible on a circuit board) or different (by way of non-limiting example, an LED with a peak excitation wavelength of about 525 nm for excitation of Cy3 dye, and an LED with a peak excitation wavelength of about 625 nm for excitation of Cy5 dye, mounted as close together as possible on a circuit board). Two-color or multicolor LED assemblies are available from, for example, LED Engin, Inc. (San Jose, Calif.) and Innovations in Optics, Inc. (Woburn, Mass.).

In some embodiments, a light source in the illumination system may be controlled electronically. By way of a non-limiting example, a light source may be synchronized with the CCD or CMOS camera so that the light source turns on when the CCD or CMOS camera begins an exposure and turns off when the camera finishes an exposure. If the illumination system contains two or more light sources, they may optionally be controlled together or independently of each other.

In some embodiments, a light source may be left on continuously. In this case, the illumination system may contain an electronically controlled shutter, and the shutter may be synchronized with the CCD or CMOS camera so that the shutter opens when the CCD or CMOS camera begins an exposure and closes when the camera finishes an exposure.

In some embodiments, the optical instrument may contain a single illumination system. In other embodiments, the instrument may contain two or more illumination systems that are identical. In yet other embodiments, the instrument may contain two or more illumination systems that are different. By way of non-limiting examples, an optical instrument for detecting fluorescence from Cy3 and Cy5 may contain one illumination system for Cy3 excitation and another illumination system for Cy5 excitation, or it may contain a single illumination system that is used for both Cy3 and Cy5 excitation.

Translation Stage

Yet another main component of the optical instrument may be one or more translation stages. One purpose of the translation stage may be to move sample holders in and out of the field view of the imaging system. Another purpose of the translation stage system may be to move the imaging system, components of the imaging system, the illumination system, or components of the illumination system relative to the sample or relative to one another, for obtaining the best possible image.

In many embodiments of the presently disclosed systems, the translation stage may further comprise a sample holder. By way of non-limiting examples, if the optical instrument is used to take images of 16-well microscope slides, the translation stage contains a slide holder. If the optical instrument is used to take images of 96-well plates or 384-well plates, and it contains a plate holder. The slide holder, plate holder, or other array support holder may be mounted on the translation stage system in any of a variety of ways known to those skilled in the art.

The translation stage may have one or more axes of motion. By way of a non-limiting example, if the support is a 16-well microscope slide and the instrument takes images of 2 adjacent wells simultaneously, a single axis of motion may be sufficient. By way of another non-limiting example, if the support is a 96-well plate and the instrument takes images of 2 adjacent wells simultaneously, then at least 2 axes of motion would be required. Additional axes of motion for adjustment of focus and tilt may also be added. If the instrument can take an image of all of the regions on the support in a single exposure, then the translation stage may be omitted in some embodiments of the optical instrument.

Housing

The systems and devices described herein can include features for insuring that the sensors of the device detect appropriate signal. For example the systems and devices can include light excluding features. The light excluding features generally reduce unintended signal from reaching light sensitive sensors. In many embodiments, one or more of the imaging system, illumination system, translation stage, and other components of the instrument are surrounded by a housing. The housing can be opaque. The housing can, in some instances, act as a faraday cage. In some instances a single housing is sufficient to exclude light from systems. The single housing can also provide external protection of the system. Alternatively, multiple housings may individually contain one or more components of the instrument. In some instances the housings are nested housings. In various embodiments, the housing can be gas and/or liquid tight.

The housing may have an access point which can exclude light from the interior of the housing. The access point may comprise materials that absorb light in the spectrum relevant to the sensors within the housing, e.g. vantablack in the visible spectrum. The access point may comprise a closure device. The closure device may be opaque. The closure device may be, e.g., a door. The closure device may be substantially light-tight in a closed position. The closure may be light-tight in a closed position.

The closure device can be opened, e.g., for insertion and removal of a 16-well slide, 96-well plate, 384-well plate, or other array support. A sensor (for example, a photointerrupter) may be used to determine whether the closure device is open or closed. The instrument's software or electronic hardware may prevent the light source in the illumination system from turning on when the closure device is open, may prevent power from being applied to the image sensor, and/or may prevent the translation stage from moving when the closure device is open.

In some embodiments, the housing may further comprise a mechanism for automated opening and closing of the closure device, as illustrated in FIGS. 10-13. The closure device can provide access to the interior of the housing. The closure device can provide access for the array to be loaded in and out of the instrument. This operation can be performed automatically. In some instances, the closure device can exclude ambient light during imaging, while opening reliably to permit loading.

In some instances the closure device does not comprise pivoting parts. In some instances the closure device does not interact with pivoting parts or latches. In some embodiments of the disclosed systems and platforms, the closure device is held by magnets to the housing. Magnets can hold the closure device to the housing in a closed position. Magnets can hold the closure device to a loading device, e.g. a tray, in an open position. During a transition from an open to closed position the closure device can transition from being primarily magnetically attached to a loading device to being primarily magnetically attached to the housing. During a transition from a closed to open position the closure device can transition from being primarily magnetically attached to the housing to being primarily magnetically attached to the loading device. In some instances the transition between the open and closed state is magnetically unstable, such instability causing the closure device to move from the transition state to either the more stable open or closed position.

The closure device can comprise a self-locating function provided by conical features on the door. The thicknesses of the parts which support the magnets on each side of a mating pair, and the depth of retaining pockets within those parts, defines the spacing between magnets in each mating pair, and thus the holding forces. The design geometry is matched to the power of the motors to provide enough retaining force, without requiring high motor torque. The system is further designed such that the motor current and speed (and hence torque) can be controlled to improve the performance, and avoid creating a safety hazard. Two of the four magnet pairs are used to temporarily hold the door to the front of the sample tray, when the tray moves outward for loading an array assembly, as depicted in FIG. 10. The other two magnet pairs are used to hold the door closed against the front panel, after the tray has moved inwards (and separated the other two magnet pairs in the process). The respective allocation of magnets is shown in FIG. 11A. The mating magnets on the front of the stage are shown in FIG. 12. The locations of the mating magnets in the front panel are shown in FIG. 13. To provide for secure grip (and therefore reliable operation), rare earth magnets provide high strength (e.g. neodymium magnets). Some embodiments of the design call for disc magnets approximately 8 mm in diameter and 3 mm thick, with the magnetic field parallel to the axis. In some embodiments, it is sufficient to replace one magnet from each pair with a weaker magnet, or with a piece of magnetic material such as iron or mild steel.

In some embodiments of the systems and platforms disclosed herein, a mechanism for providing for automated door or lid closure on one or more instrument compartments is provided, wherein the mechanism comprises: (a) a closure; (b) a housing which magnetically holds the closure in a first position; and (c) a translation stage which magnetically holds the closure in a second position. In some embodiment, the mechanism further comprises a gasket positioned between the closure and the housing. In some embodiments of the mechanism, the gasket is attached to the closure. In other embodiments, the gasket is attached to the housing. In some embodiments, the closure and housing are substantially opaque, and the gasket creates a substantially light-tight seal between the closure and the housing in the first position. In some embodiments of the mechanism, one or more magnets are positioned to hold the closure onto the housing in the first position. In some embodiments of the mechanism, one or more magnets are positioned to hold the closure onto a first surface of the translation stage in the second position. In some embodiments, the mechanism further comprises two or more pairs of mating locating features to align the closure with the translation stage in the second position. In some embodiments, the mechanism further comprises two or more pairs of mating locating features to align the closure with the housing in the first position. In some embodiments of the mechanism, the pairs of mating locating features comprise conical pins and conical holes. In some embodiments, the housing comprises an optical instrument. In some embodiments, the translation stage includes a sample holder. In some embodiments, the sample holder is designed to hold a microscope slide, a microarray, or a microwell plate. In some embodiments, the closure is not hinged. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of fasteners such as screws or clips. In some embodiments, the closure is not attached to either the housing or the translation stage through the use of an adhesive.

Image Data

The methods, systems, and platforms described herein for counting one or more labeled features on an array may comprise data input, or use of the same. The data input may comprise imaging information and/or images of one or more regions of arrays. The images comprise pixel data, wherein each unit of pixel data may be encoded in, by way of non-limiting examples, 4, 8, 12, 14, 16, 32, 64, 128, 256, or more bits. An image may encompass one or more regions of an array. The spatial resolution of an image may be determined by the spatial resolution of the optical instrument, but in some embodiments of the disclosed methods and systems, spatial resolution may be enhanced by digital image processing schemes based on, by way of non-limiting examples, interpolations, extrapolations, modeling, and/or transforms.

The methods, systems, and platforms described herein for counting one or more labeled features on an array may comprise acquisition and analysis of images of one, two, or more distinct regions on an array. In some embodiments, two or more regions to be imaged may overlap, partially overlap, or not overlap at all. Furthermore, two or more regions to be imaged may be adjacent, or non-adjacent.

The methods, software, systems, and platforms described herein for counting one or more labeled features on an array may comprise acquisition and analysis of images of all or a portion of an array. In some embodiments, the region of an array that is imaged may comprise at least about 1% of the total area of the array. In some embodiments, the region of the array that is imaged image may comprise at least about 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10% or more of the total area of the array. In other embodiments, the region of the array to be imaged may comprise at least about 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24%, 25% or more of the total area of the array. In still other embodiments, the region of the array to be imaged may comprise at least about 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70% or more of the total area of the array. In some embodiments, the region of the array to be imaged may comprise at least about 75%, 80%, 85%, 90%, 92%, 95%, 97% or more of the total area of the array.

The methods, software, systems, and platforms described herein for counting one or more labeled features on an array may comprise acquisition and analysis of images of all or a portion of the features of an array. In some embodiments, the image may encompass between 10% and 100% of the total number of features on the array. In some embodiments, the image may encompass at least 5%, at least 10%, at least 20%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or at least 95% of the total number of features on the array. In some embodiments, the image may encompass at most 95%, at most 90%, at most, 80%, at most 70%, at most 60%, at most 50%, at most 40%, at most 30%, at most 20%, at more 10%, or at most 5% of the total number of features on the array. The number of features encompassed by the image may fall within any range bounded by any of these values (e.g. from about 15% to about 90% of the total number of features of the array).

Image Acquisition

The methods, systems, and platforms described herein comprise software for acquiring images from an optical instrument. In some embodiments, e.g. for optical instruments comprising two or more image sensors, the image acquisition may operate in a parallel mode, i.e. where two or more images are acquired simultaneously. Alternatively, the image acquisition may operate in a serial mode, where two or more images are acquired sequentially. In general, image acquisition may be performed in a continuous fashion (i.e., wherein the image is acquired within a single exposure time period) or intermittently (i.e., wherein the image is acquired in a discontinuous fashion, e.g. using two or more separate exposure time periods, wherein in some embodiments two more images are combined for signal averaging purposes).

In a non-limiting example, an array may comprise 16 wells where an image is formed for each well. The image acquisition module may sequentially read the 16 images. Reading the 16 images can be completed in a continuous time period; or, the system may read a first image followed by analyzing the first image, and then the procedure of image reading and image analysis repeats till the 16th image is analyzed. Alternatively, the image acquisition module may read a pair of images at once, and repeat the reading till all the 16 images are acquired. The 16 images may be read sequentially in a single time period. In some applications, a pair of images may be read, followed by immediate image analyses.

Image Analysis

In general, one of the objectives in performing image processing and analysis is to improve signal-to-noise ratios and quantitation. In an ideal array experiment, labeled features comprising bound target molecules and/or labels would produce a uniform, non-saturated signal level when imaged and non-labeled features would appear uniformly dark, with a signal level of close to zero. In reality, a variety of artifacts due to instrumental and/or assay procedural issues including, but not limited to, stray light, background fluorescence (in the case of fluorescence-based imaging), particulate contaminants, and non-specific binding of assay components, can produce images that hinder one's ability to extract quantitative signal intensity data and make definitive calls as to which features of the array are labeled. Accordingly, the methods, systems, and platforms disclosed herein may comprise software for performing a variety of image processing tasks including, but not limited to, feature location, image orientation correction, background correction, intensity measurement, data scaling, data thresholding, and data analysis functions.

Image orientation and location of features. In some embodiments, fiducial features incorporated into the design of an array are used to orient the image and locate features in an automated fashion using custom image analysis software. By way of non-limiting example, the microarray pattern shown in FIGS. 15 and 16 consists of a 32×32 array of features, where fiducial features in the top and bottom rows permit location of the array in the digital images. The fiducial features are typically arranged in an asymmetric pattern whose orientation is readily identifiable, e.g. fiducial features located in the top row of features in an array such as that depicted in FIG. 16 may comprise a distinctive pattern for which the left and right ends of the row are asymmetric, while the pattern of fiducial features in the bottom row is typically different from that in the top row. This permits easy manual and automatic identification of incorrect placement of the array, and also facilitated detection of imaging problems. In some embodiments, the image may be transformed also transformed so that the apparent orientation of the images corresponds to the orientation as viewed by a user, often referred to as the viewing reference orientation, as shown in FIG. 14 for a specific embodiment of an array designed for use with the methods, systems, and platforms disclosed herein.

Refinement of feature locations. In some embodiments, the measured location of each feature is refined so as to account for array fabrication errors, which can produce offsets of several image pixels. The locations of features obtained during the initial image orientation and feature location step may be used to subdivide the array or array region into analysis windows, for example an array may be divided into 32×32 analysis windows, wherein each analysis window comprises an image area of 12×12 pixels centered on each feature, as shown in FIG. 19. The size of the analysis window used is dependent on the size of the features on the array, and may be any size that is necessary to correctly locate and distinguish between features and background regions on the array. By way of non-limiting examples, the analysis window may be defined as a 5×5, 7×7, 9×9, 15×15, 51×51, or 101×101 pixel area that is centered on the array feature. The position of the feature within the window may be determined on the basis of the signal intensity distribution and clustering of the pixels within the analysis window. The refined location of the feature is calculated as an offset in coordinates X and Y from the site predicted by a perfect rectilinear grid. In some embodiments, distortion of the feature location results due to defects such as dust is avoided by making use of the correlation between printing artifacts between different arrays on the same substrate. Since the printing artifacts are typically consistent, the correction relative to a hypothetical rectilinear grid is also consistent. The feature location optimization results for a given feature are combined across all of the arrays being analyzed, and the median offset is used for subsequent analysis, which greatly decreases noise in the final experimental results.

Local background correction. Once the feature pixel set “S” and background pixel set “B” have been defined for each location in the array (for example, see FIG. 20), the local background is removed via a calculation involving signal intensity and background intensity statistics. Examples of suitable signal and background intensity statistics for use in local background correction calculations include, but are not limited to, the mean, the median, or a ratio of signal-to-background. In some embodiments, following feature location refinement performed as described above, the pixels within the analysis window are assigned to be signal pixels, background pixels, or transitional pixels, i.e. pixels to be disregarded, in subsequent calculations of signal and background intensity statistics (see FIG. 20). In some embodiments of the disclosed methods, local background correction is performed via subtraction in logarithm space, i.e. a calculation that is closely related to a signal-to-background ratio calculation, as illustrated in a non-limiting example below:

Given the 16-bit pixel data measurements for a defined feature and background area, on next calculates a single value S for the signal pixels and a value B for the background pixels respectively. One useful statistic is the median value for each set of pixels, i.e.

S=the median of the pixel values for the set of pixels “S”

B=the median of the pixel values for the set of pixels “B”

Various other statistics could be used in this situation, such as the mean of the set of values, or a nominated percentile within the set. It is not necessary, and may not be optimal, to use the same statistic for both S and B. For example, low data noise and strong separation between “on” and “off” data points can be obtained by using:

S=the median of the pixel values for the set of pixels “S”, and

B=the 25^(th) percentile of the pixel values for the set of pixels “B”.

As a further enhancement, the particular percentile used can be a pre-stored and re-configurable parameter stored in a settings file. The background-corrected intensity statistic for each spot is:

I=log₂(16 S )−log₂(16 B )

An example of a scatter plot (intensity statistic vs feature number) and histogram of intensity data are shown in FIG. 21. In this example, the background is corrected for by performing a subtraction of logarithms, such that the intensity metric is related to a ratio of S and B. In some situations, a linear subtraction (e.g. I=S−B) is preferable. Once the background-corrected intensity statistics have been calculated for the complete set of features, the next task is to determine which of the features are labeled (i.e. “on”, or “positive”) and which are non-labeled (i.e. “off” or “negative”). This is accomplished by determining a signal intensity threshold value based on a statistical analysis of the local background-corrected feature intensities, and subsequently counting how many features, k, have background-corrected signal intensities that are larger than this threshold level. The signal intensity threshold may be considered a “dynamic” signal intensity threshold in that the threshold is determined through analysis of the data from the current experiment, and thereby eliminates potential errors due to such factors as instrumental drift and variations in assay procedure.

Determination of dynamic signal intensity thresholds. In many embodiments of the methods, systems, and platforms disclosed herein, a dynamic signal intensity threshold is determined for one or more regions of an array by performing one or more statistical analyses of the background corrected signal intensity data for the complete set of features. Any of a variety of statistical (or empirical) analysis techniques may be used, including but not limited to, k-means clustering, k-medoids clustering, mixture model statistical analysis, probe reference distribution methods, or empirical analysis based on sorting of background corrected signal intensity values, sorting of pairwise differences in background corrected signal intensity values, etc. In some embodiments, analyses may utilize spatial and/or temporal information collected across multiple analysis windows, across multiple array regions, or over specified periods of time, or combinations thereof, to improve the quality of the analysis and thereby improve the quantitative aspects of the disclosed methods. In some embodiments, other sources of information, including, but not limited to, for example, locations of probes, frequently occurring artifact patterns, previously derived results, literature reports, array manufacturers' suggestions, human knowledge, and/or human guidance may also be integrated into the analysis.

By way of a non-limiting example of threshold determination, in some embodiments of the disclosed methods, the background corrected signal intensity threshold may be determined using an empirical approach (e.g. the “E-Derivative” approach; see FIG. 22) wherein the background corrected signal intensity data for the complete set of array features constitutes a set I={I_(i)}. The set I is sorted in increasing order to obtain a set of ordered corrected signal intensity values z={z_(i)}={Sort[y_(i)]}. Next, the differences between each sorted array value are calculated to obtain d={d₁, d₂, . . . , d_(m)}, where d_(i)=z_(i+1)−z_(i). The intensity differences are then smoothed using a “window” whose width is w, to produce a smoothed, sorted array s:

$s_{j} = \frac{\sum\limits_{i = {j - w}}^{j + w}d_{i}}{{2w} + 1}$

The threshold is T, the point for which the slope of the smoothed, sorted data is steepest (see FIG. 21):

T=max(s _(j))

The number of features, k, which are “on” (or labeled) is:

k=Σ _(i=1) ^(m) I[I _(i) >T].

By way of another non-limiting example of threshold determination, in some embodiments the background corrected signal intensity threshold may be determined by fitting the background corrected feature intensity data to two more assumed distributions (i.e. a “Mixture Model” approach), wherein the assumed distributions comprise normal distributions, uniform distributions, etc. The mixture model approach essentially models the underlying process that generated the data, by assuming that the positive feature intensities are generated from a positive feature distribution with higher average signal intensity, and the negative feature intensities are generated from a negative feature distribution with lower average signal intensity. This approach additionally models the variability in the feature intensities generated by each distribution, which can be useful in cases where the negative feature intensities tend to be much less variable, while the positive feature intensities tends to be much more variable. The choice of the distributions is determined by the shape of the data curve in a background corrected feature intensity histogram. The parameters of the model, e.g. the estimated average intensities for “on” and “off” features and their corresponding variance, are estimated from the data using a method such as the Expectation Maximization algorithm.

By way of another non-limiting example of threshold determination, in some embodiments the background corrected signal intensity threshold may be determined by fitting the background corrected feature intensity data to a model function comprising three assumed distributions (i.e. a “3-Component Model” approach), wherein the assumed distributions comprise a log-normal distribution, Dist1, for the “off” spots, a normal distribution, Dist2, for the “on” spots, and a flat offset FlatLevel. Adjustable parameters for the model include: (i) the number of bins in the starting histogram, (ii) Dist1 amplitude, (iii) Dist1 position, (iv) Dist1 standard deviation, (v) Dist2 amplitude, (vi) Dist2 position, (vii) Dist2 standard deviation, and (viii) FlatLevel. An example fit to histogram data is shown in FIG. 23. One non-limiting example of a method to determine the threshold after fitting feature intensity data to such a distribution is as follows: (i) fit the 3-component distribution to the histogram data, and (ii) set the threshold T by calculating the following values: (1) the intensity t_(low) where the high-intensity side of the fitted log-normal distribution component drops below 1 (or a defined parameter for comparison), (2) the intensity t_(subflat) where the high-intensity side of the fitted log-normal distribution component drops below the fitted FlatLevel result, (3) the intensity t_(subnorm) where the high-intensity side of the fitted log-normal distribution component drops below the value of the fitted normal distribution at that histogram bin, and (4) choosing T=min[t_(low), t_(subflat), t_(subnorm)]. Alternative approaches for determining a threshold using a 3-component model approach will be apparent to those of skill in the art. It can be beneficial to calculate starting values of model parameters, to improve the speed and reliability of the modelling process, which can be achieved using methods such as a coarse search to identify the dominant peaks in the histogram, or based on assumptions derived from typical historical data sets.

By way of another non-limiting example of threshold determination, in some embodiments the background corrected signal intensity threshold may be determined using a “Peak Split Fiducials” approach. This approach, which copes well with low-quality data, is described as follows. An initial split of the feature intensity data into high and low intensity groups is made using the scale defined naturally by the spread between “on” (label present) and “off” (label absent) features in the fiducial rows. Then, the histogram peak (after optionally smoothing the data using standard methods such as a moving average filter) is found for each group. The threshold is then determined by examining the spread in the intensity data around the low-intensity group peak. Define upper and lower bounds of fiducial intensity: (i) F_(off)=[median of OFF fiducials], (ii) F_(on)=[median of ON fiducials], and (iii) F_(range)=F_(on)−F_(off). Perform an initial split of the data based on the fiducial scale, at the level Splitvalue=F_(off)+PeakSplit×F_(range), where the parameter PeakSplit is a percentage of F_(range). Find 2 peaks: (i) Peak1=the intensity peak for which the histogram is a maximum, for all features of intensity less than Splitvalue, (ii) Peak2=the intensity peak for which the histogram is a maximum, for all features of intensity greater than Splitvalue. Calculate the standard deviation, Stdev1, of all the features in the neighbourhood of Peak1, defined as all index features from the lowest intensity up to Peak1+PeakOffsetFraction×(Peak2−Peak1), where PeakOffsetFraction is an adjustable parameter. Set the threshold to the lesser of T_(psf) and T_(LocMin), which are calculated as follows: (i) T_(psf)=Peak1+StdevMultiple Stdev1, where StdevMultiple is a parameter, OR T_(LocMin)=the intensity corresponding to the minimum of a smoothed histogram curve between Peak1 and T_(psf). Similar approaches using different methods for determining the spread around either peak can also be used.

The methods and systems disclosed herein may comprise detecting one or more labeled features within one or more regions on an array. In some embodiments, detecting a labeled feature within a region may comprise comparing the background corrected signal intensity for a feature with a dynamic signal intensity threshold derived through statistical analysis of the background corrected signal intensities for the complete set of features. When the background corrected signal intensity for a given feature is above the threshold, the feature may be classified as a labeled feature. Alternatively, if the background corrected signal intensity for a given feature is below the threshold, the feature may be classified as non-labeled. Application of a background corrected signal intensity threshold to the corrected signal intensity data for the complete set of features thus constitutes a binary transformation of the data to a digital output wherein features are classified as either labeled (“on”) or non-labeled (“off”). Those of skill in the art will recognize that there are many possible variations in the type and order of analysis steps that may be applied to achieve this binary transformation.

Calculation of the absolute number of target molecules in a sample. The absolute number of target molecules in a sample, wherein the target molecules have been labeled in a stochastic fashion as described previously, may be determined using arrays comprising feature sets comprising probes that are specific for the labels in the stochastic label set. Following hybridization or binding of the target molecules or labeled target molecules to the array, the array is imaged and processed as described above, and the number of target molecules, N, in the sample is determined from the number, k, of labeled features based on Poisson distribution statistics:

$N = {{- m}*{\log\left( {1 - \frac{k}{m}} \right)}}$

where m is the total number of features (i.e. the total number of unique labels in the set of stochastic labels).

Quality metrics. In some embodiments, it is beneficial to include a numerical measure of the quality of the data, to help to gauge the success of an experiment. In some embodiment, this quality measurement may be based on statistics from the feature-by-feature intensity data. One simple quality measurement Q_(Sep1) is simply the difference between the means of the positive and negative features intensities, after background correction and scaling, i.e. Q_(Sep1)=(mean intensity of features having an intensity above the signal intensity threshold)−(mean intensity of features having an intensity below the threshold). In some embodiments, this metric may also incorporate the spread in the intensities of the feature distribution(s) by scaling the difference between means by the standard deviation of each distribution, e.g. Q_(Sep2)=Q_(Sep1)/(standard deviation of intensities for feature having intensities below the threshold intensity). Other quality measurements can be constructed based on the separation and breadth of modelled distributions which are fitted to the experimental data. In some embodiments, deviance measurement may be used for a quality metric (FIG. 24); this is a calculation based on the degree of separation between two fitted normal distributions. In some embodiments, it is preferable to empirically determine a dynamic intensity threshold by setting the threshold to a value which maximizes a quality metric.

Confidence intervals. In some embodiments of the methods disclosed herein, it is beneficial to define confidence intervals (see Dube, et al. (2008), PLoS ONE 3(8): e2876 for a more complete description) when specifying estimates of the absolute number of target molecules detected in a sample using the techniques described above. The 95% confidence interval of the estimation of N from stochastic labeling experiments can be derived from k for a single reaction employing a single set of _(m) distinct labels. The 95% confidence interval for N ranges from N_(low) to N_(high), where

${N_{low} = {{- m} \times {\ln\left\lbrack {1 - \left( {\frac{k}{m} - {1.96\sqrt{\frac{\frac{k}{m}\left( {1 - \frac{k}{m}} \right)}{m}}}} \right)} \right\rbrack}}},{and}$ $N_{high} = {{- m} \times {\ln\left\lbrack {1 - \left( {\frac{k}{m} + {1.96\sqrt{\frac{\frac{k}{m}\left( {1 - \frac{k}{m}} \right)}{m}}}} \right)} \right\rbrack}}$

Ratio of the number of copies of a target molecule in two samples. Frequently, researchers seek to compare the expression levels of genes in different samples, by calculating a ratio between gene expression levels in two or more samples. Using calculations such as those described above, it is possible to derive confidence intervals for such ratios where the number of target molecules in each sample are determined using the methods, systems, and platforms as disclosed herein.

Replicate experiments. The benefit of performing replicate experiments, and the proper calculation of associated uncertainties, is illustrated in FIG. 25. While results (blue points) from replicate experiments can simply be combined (blue error bars), calculating the uncertainty from Poisson statistics, wherein one considers the replicates as comprising a larger pool of labels, gives the smaller green error bars illustrated in the figure. The accuracy of this estimation will vary depending on the consistency between replicates, and there is a numerical simplification employed in considering the labels of replicate experiments to be a pool of diverse labels. Therefore, in some embodiments of the disclosed methods, different methods for calculating confidence intervals may be more appropriate at high ratios of k/m.

User Interface

The methods, software, systems, and platforms disclosed herein may comprise a user interface, or use of the same. The user interface may provide one or more inputs from a user. The input from the user interface may comprise instructions for counting the one or more labeled features in a real time mode. The input from the user interface may comprise instructions for counting the one or more features from one or more images. The one or more images may be archived images. The one or more images may be live captured images.

Different platform operators may have their own preferences about the timing to analyze images. One platform operator may want to run the image analyses while live capturing images. Another platform operator may run the image analyses after all the images have been collected. Or, another platform operator may run the image analyses on a set of archived images. These options can be selected via inputs to the user interface.

Digital Processing Device

The methods, software, systems, and platforms disclosed herein may comprise a digital processing device, or use of the same. The digital processing device may comprise one or more hardware central processing units (CPU) that carry out the device's functions. The digital processing device may comprise an operating system configured to perform executable instructions. The digital processing device may be connected to a computer network. The digital processing device may be connected to the Internet such that it accesses the World Wide Web. The digital processing device may be connected to a cloud computing infrastructure. The digital processing device may be connected to an intranet. The digital processing device may be connected to a data storage device.

Suitable digital processing devices may include, by way of non-limiting examples, server computers, desktop computers, laptop computers, notebook computers, sub-notebook computers, netbook computers, netpad computers, set-top computers, handheld computers, Internet appliances, mobile smartphones, tablet computers, personal digital assistants, video game consoles, and vehicles. In some instances, smartphones may be suitable for use in the system described herein. In some instances, select televisions, video players, and digital music players with optional computer network connectivity may be suitable for use in the system described herein. Suitable tablet computers may include those with booklet, slate, and convertible configurations, known to those of skill in the art.

The digital processing device may comprise an operating system configured to perform executable instructions. The operating system may be software, including programs and data, which manages the device's hardware and provides services for execution of applications. Suitable server operating systems may include, by way of non-limiting examples, FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle® Solaris®, Windows Server®, and Novell® NetWare®. Suitable personal computer operating systems may include, by way of non-limiting examples, Microsoft® Windows®, Apple® Mac OS X®, UNIX®, and UNIX-like operating systems such as GNU/Linux®. The operating system is provided by cloud computing. Suitable mobile smart phone operating systems may include, by way of non-limiting examples, Nokia® Symbian® OS, Apple® iOS®, Research In Motion® BlackBerry OS®, Google® Android®, Microsoft Windows Phone® OS, Microsoft® Windows Mobile® OS, Linux®, and Palm WebOS®.

The digital processing device may comprise a storage and/or memory device. The storage and/or memory device may be one or more physical apparatuses used to store data or programs on a temporary or permanent basis. The digital processing device may be a volatile memory and may require power to maintain stored information. The digital processing device may be a non-volatile memory and may retain stored information when the digital processing device is not powered. The non-volatile memory may comprise flash memory. The non-volatile memory may comprise dynamic random-access memory (DRAM). The non-volatile memory may comprise ferroelectric random access memory (FRAM). The non-volatile memory may comprise phase-change random access memory (PRAM). The storage device may include, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, magnetic disk drives, magnetic tapes drives, optical disk drives, and cloud computing based storage. The storage and/or memory device may be a combination of devices such as those disclosed herein.

The digital processing device may comprise a display. The display may be used to send visual information to a user. The display may be a cathode ray tube (CRT). The display may be a liquid crystal display (LCD). The display may be a thin film transistor liquid crystal display (TFT-LCD). The display may be an organic light emitting diode (OLED) display. The OLED display may be a passive-matrix OLED (PMOLED) or active-matrix OLED (AMOLED) display. The display may be a plasma display. The display may be a video projector. The display may be a combination of devices such as those disclosed herein.

The digital processing device may comprise an input device to receive information from a user. The input device may be a keyboard. The input device may be a pointing device including, by way of non-limiting examples, a mouse, trackball, track pad, joystick, game controller, or stylus. The input device may be a touch screen or a multi-touch screen. The input device may be a microphone to capture voice or other sound input. The input device may be a video camera to capture motion or visual input. The input device may be a combination of devices such as those disclosed herein.

Non-Transitory Computer Readable Storage Medium

The methods, software, systems, and platforms disclosed herein may comprise one or more non-transitory computer readable storage media encoded with a program including instructions executable by the operating system of an optionally networked digital processing device. A computer readable storage medium may be a tangible component of a digital processing device. A computer readable storage medium may be optionally removable from a digital processing device. A computer readable storage medium may include, by way of non-limiting examples, CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic disk drives, magnetic tape drives, optical disk drives, cloud computing systems and services, and the like. The program and instructions may be permanently, substantially permanently, semi-permanently, or non-transitorily encoded on the media.

Computer Programs (General)

The methods, software, systems, and platforms disclosed herein may comprise at least one computer processor, or use of the same. The computer processor may comprise a computer program. A computer program may include a sequence of instructions, executable in the digital processing device's CPU, written to perform a specified task. Computer readable instructions may be implemented as program modules, such as functions, features, Application Programming Interfaces (APIs), data structures, and the like, that perform particular tasks or implement particular abstract data types. A computer program may be written in various versions of various languages.

The functionality of the computer readable instructions may be combined or distributed as desired in various environments. A computer program may comprise one sequence of instructions. A computer program may comprise a plurality of sequences of instructions. A computer program may be provided from one location. A computer program may be provided from a plurality of locations. A computer program may include one or more software modules. A computer program may include, in part or in whole, one or more web applications, one or more mobile applications, one or more standalone applications, one or more web browser plug-ins, extensions, add-ins, or add-ons, or combinations thereof.

Web Applications

A computer program may include a web application. In light of the disclosure provided herein, those of skill in the art will recognize that a web application may utilize one or more software frameworks and one or more database systems. A web application may be created upon a software framework such as Microsoft .NET or Ruby on Rails (RoR). A web application may utilize one or more database systems including, by way of non-limiting examples, relational, non-relational, feature oriented, associative, and XML database systems. Suitable relational database systems may include, by way of non-limiting examples, Microsoft® SQL Server, mySQL™, and Oracle®. Those of skill in the art will also recognize that a web application may be written in one or more versions of one or more languages. A web application may be written in one or more markup languages, presentation definition languages, client-side scripting languages, server-side coding languages, database query languages, or combinations thereof. A web application may be written to some extent in a markup language such as Hypertext Markup Language (HTML), Extensible Hypertext Markup Language (XHTML), or eXtensible Markup Language (XML). A web application may be written to some extent in a presentation definition language such as Cascading Style Sheets (CSS). A web application may be written to some extent in a client-side scripting language such as Asynchronous Javascript and XML (AJAX), Flash® Actionscript, Javascript, or Silverlight®. A web application may be written to some extent in a server-side coding language such as Active Server Pages (ASP), ColdFusion®, Perl, Java™, JavaServer Pages (JSP), Hypertext Preprocessor (PHP), Python™, Ruby, Tcl, Smalltalk, WebDNA®, or Groovy. A web application may be written to some extent in a database query language such as Structured Query Language (SQL). A web application may integrate enterprise server products such as IBM® Lotus Domino®. A web application may include a media player element. A media player element may utilize one or more of many suitable multimedia technologies including, by way of non-limiting examples, Adobe® Flash®, HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, Java™, and Unity®.

Mobile Applications

A computer program may include a mobile application provided to a mobile digital processing device. The mobile application may be provided to a mobile digital processing device at the time it is manufactured. The mobile application may be provided to a mobile digital processing device via the computer network described herein.

A mobile application may be created by techniques known to those of skill in the art using hardware, languages, and development environments known to the art. Those of skill in the art will recognize that mobile applications may be written in several languages. Suitable programming languages include, by way of non-limiting examples, C, C++, C#, Featureive-C, Java™, Javascript, Pascal, Feature Pascal, Python™, Ruby, VB.NET, WML, and XHTML/HTML with or without CSS, or combinations thereof.

Suitable mobile application development environments may be available from several sources. Commercially available development environments include, by way of non-limiting examples, AirplaySDK, alcheMo, Appcelerator, Celsius, Bedrock, Flash Lite, .NET Compact Framework, Rhomobile, and WorkLight Mobile Platform. Other development environments may be available without cost including, by way of non-limiting examples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile device manufacturers distribute software developer kits including, by way of non-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK, BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, and Windows® Mobile SDK.

Those of skill in the art will recognize that several commercial forums may be available for distribution of mobile applications including, by way of non-limiting examples, Apple® App Store, Android™ Market, BlackBerry® App World, App Store for Palm devices, App Catalog for webOS, Windows® Marketplace for Mobile, Ovi Store for Nokia® devices, Samsung® Apps, and Nintendo® DSi Shop.

Standalone Applications

A computer program may include a standalone application, which may be a program that may be run as an independent computer process, not an add-on to an existing process, e.g., not a plug-in. Those of skill in the art will recognize that standalone applications may be often compiled. A compiler may be a computer program(s) that transforms source code written in a programming language into binary feature code such as assembly language or machine code. Suitable compiled programming languages include, by way of non-limiting examples, C, C++, Featureive-C, COBOL, Delphi, Eiffel, Java™, Lisp, Python™, Visual Basic, and VB .NET, or combinations thereof. Compilation may be often performed, at least in part, to create an executable program. A computer program may include one or more executable complied applications.

Web Browser Plug-Ins

A computer program may include a web browser plug-in. In computing, a plug-in may be one or more software components that add specific functionality to a larger software application. Makers of software applications may support plug-ins to enable third-party developers to create abilities which extend an application, to support easily adding new features, and to reduce the size of an application. When supported, plug-ins may enable customizing the functionality of a software application. For example, plug-ins are commonly used in web browsers to play video, generate interactivity, scan for viruses, and display particular file types. Those of skill in the art will be familiar with several web browser plug-ins including, Adobe® Flash® Player, Microsoft® Silverlight®, and Apple® QuickTime®. The toolbar may comprise one or more web browser extensions, add-ins, or add-ons. The toolbar may comprise one or more explorer bars, tool bands, or desk bands.

In view of the disclosure provided herein, those of skill in the art will recognize that several plug-in frameworks may be available that enable development of plug-ins in various programming languages, including, by way of non-limiting examples, C++, Delphi, Java™, PHP, Python™, and VB .NET, or combinations thereof.

Web browsers (also called Internet browsers) may be software applications, designed for use with network-connected digital processing devices, for retrieving, presenting, and traversing information resources on the World Wide Web. Suitable web browsers include, by way of non-limiting examples, Microsoft® Internet Explorer®, Mozilla® Firefox®, Google® Chrome, Apple® Safari®, Opera Software® Opera®, and KDE Konqueror. The web browser may be a mobile web browser. Mobile web browsers (also called mircrobrowsers, mini-browsers, and wireless browsers) may be designed for use on mobile digital processing devices including, by way of non-limiting examples, handheld computers, tablet computers, netbook computers, subnotebook computers, smartphones, music players, personal digital assistants (PDAs), and handheld video game systems. Suitable mobile web browsers include, by way of non-limiting examples, Google® Android® browser, RIM BlackBerry® Browser, Apple® Safari®, Palm® Blazer, Palm® WebOS® Browser, Mozilla® Firefox® for mobile, Microsoft® Internet Explorer® Mobile, Amazon® Kindle® Basic Web, Nokia® Browser, Opera Software® Opera® Mobile, and Sony® PSP™ browser.

Software Modules (General)

The methods, software, systems, and platforms disclosed herein may comprise one or more software, servers, and database modules, or use of the same. In view of the disclosure provided herein, software modules may be created by techniques known to those of skill in the art using machines, software, and languages known to the art. The software modules disclosed herein may be implemented in a multitude of ways. A software module may comprise a file, a section of code, a programming feature, a programming structure, or combinations thereof. A software module may comprise a plurality of files, a plurality of sections of code, a plurality of programming features, a plurality of programming structures, or combinations thereof. The one or more software modules may comprise, by way of non-limiting examples, a web application, a mobile application, and a standalone application. Software modules may be in one computer program or application. Software modules may be in more than one computer program or application. Software modules may be hosted on one machine. Software modules may be hosted on more than one machine. Software modules may be hosted on cloud computing platforms. Software modules may be hosted on one or more machines in one location. Software modules may be hosted on one or more machines in more than one location.

Databases

The methods, software, systems, and platforms disclosed herein may comprise one or more databases, or use of the same. In view of the disclosure provided herein, those of skill in the art will recognize that many databases may be suitable for storage and retrieval of imaging information. Suitable databases may include, by way of non-limiting examples, relational databases, non-relational databases, feature oriented databases, feature databases, entity-relationship model databases, associative databases, and XML databases. A database may be internet-based. A database may be web-based. A database may be cloud computing-based. A database may be based on one or more local computer storage devices.

EXAMPLES

The following illustrative examples are representative of specific embodiments of the methods, systems, and platforms described herein, but are not meant to be limiting in any way.

Example 1—Optical Instrument

FIG. 1 shows one embodiment of the optical instrument. This embodiment was used for simultaneously imaging 2 adjacent wells of a 16-well microscope slide. Each well contained 1024 (32×32) features, also called spots, which may be labeled with fluorescence. A spot diameter was approximately 80 microns. Center-to-center distance between adjacent spots was 161 microns. The purpose of the instrument was to determine the brightness of each spot. FIG. 1E shows the translation stage system 105, imaging system 106, and illumination system 107. The translation stage system contained a single-axis translation stage which was constructed from a Misumi model SSELBW9-170 recirculating ball slide driven by a Haydon Kerk 26000-series linear actuator. A holder for a 16-well microscope slide was mounted on the translation stage. The linear actuator was controlled by a Peter Norberg Consulting model BC2D20-0700 motion controller. FIG. 1G shows a USB hub 112, custom circuit board 113, and a motion controller 114. The motion controller and the CCD camera were USB devices. The USB hub allowed communication between a computer and the instrument to take place over a single USB cable. The custom circuit board contained a Luxdrive model 3021-D-E-1000 LED driver. The custom circuit board contained a logic chip to synchronize the LED with the CCD camera (turn the LED on when the CCD camera starts an exposure and off when the CCD camera finishes an exposure) and to prevent the LED from turning on when the instrument's door is open.

Example 2—Imaging System

An embodiment of an imaging system is illustrated in FIG. 2. Light emitted by dye molecules on a surface of the support 205 was collimated by an achromatic cemented doublet lens 204, filtered by a bandpass filter 203, and focused by a camera lens 202 onto the sensor 201 of a CCD camera. Lens 204 (Edmund Optics model 47640) had a focal length of 85 mm and a diameter of 25 mm. Filter 203 (Semrock model FF01-593/40-25) was an emission bandpass filter for use with cy3 or phycoerythrin dye. Lens 202 (Fujinon model HF25HA-1B) has a focal length of 25 mm. Lens 202 was a multi-element lens, but it is shown in FIG. 2 as an infinitesimally thin single-element lens because the design details of the multi-element lens were proprietary to Fujinon. The adjustable aperture stop of lens 202 was set to 2.8. The CCD camera (Point Grey Research model CMLN-13S2M-CS) had 1296×964 pixels and a pixel size of 3.75 microns. In this embodiment only the central 1280×640 pixels were used. The camera's plastic housing was removed and the camera's circuit board was cooled by a small fan. Lenses 204 and 202 formed a finite-conjugate imaging system with a magnification of 0.3.

Example 3—Illumination System

An embodiment of an illumination system is illustrated in FIG. 3. Light emitted by light source 301 was collimated by lens 302 and then passed through aperture 303, bandpass filter 304, and lenses 305, 306, and 307, before reaching sample 308. Light source 301 (LedEngin model LZ4-40G100) was an LED with a peak emission wavelength of approximately 525 nm. Lens 302 (Thorlabs model ACL2520-A) was an aspheric lens with a diameter of 25 mm and a focal length of 20 mm. Aperture 303 (Fotofab custom part) was a rectangular hole (19 mm×7.5 mm) in a 25-mm-diameter steel disk. Filter 304 (Semrock model FF01-531/40-25) was an excitation bandpass filter for use with cy3 or phycoerythrin dye. Lenses 305, 306, and 307 were plano-convex lenses with diameters of 25 mm and focal lengths of 60 mm. Lenses 301 and 302 formed a finite-conjugate imaging system with a magnification of 3 and imaged light source 301 onto the pupils of lenses 306 and 307. Lenses 306 and 307 formed a finite-conjugate imaging system with a magnification of 1 and imaged aperture 303 onto sample 308. The illumination system was tilted at 45 degrees with respect to sample 308. The illuminated area was approximately 19 mm×10.6 mm, where 10.6 mm (=7.5 mm/cosine (45 degrees)).

Example 4—Reference Probe Preparation

The purpose of this experiment was to illustrate the use of an ad hoc method to count the number of hybridizations taking place on an array. This example used probes that the specific DNA sequences attached to an array. The 32×32 feature arrays used in this experiment contain 960 different measure spots along with 32 positive control probes and 32 negative control probes (see FIGS. 15 and 16). The 32 positive control probes were used to ensure actual binding can occur by using stock oligonucleotide, while the 32 negative control probes contained empty spots with no probes at all. In the image analysis step, we considered a probe to have intensity above the set intensity threshold, then we referred to the probe as a positive probe, while if the probe intensity was below the set intensity threshold, we referred to the probe as a negative feature. Positive probes were assumed to measure whether there was a significant amount of corresponding complementary oligonucleotide in the sample, while negative features represented absent oligonucleotides. The positive probes were otherwise referred to as labels, meaning we can count up to 960 unique labels or barcodes, to measure 960 copies of oligonucleotides in the sample, which can then be further generalized to predict the actual amount of oligonucleotides in the original sample. Depending on the experiment, out of the M total labels, or 960 total labels, we could calculate the total number of copies, N, of the oligonucleotides in the sample, by predicting N from the actual observed unique barcodes or number of positive probes, k.

Example 5—Threshold Computation

The purpose of this experiment was to demonstrate one method to compute a threshold for discriminating between labeled and non-labeled features on an array.

-   -   I. Set I_(LL), intensity lower limit, I_(UL), intensity upper         limit, and w, window size.     -   II. Obtain a set of feasible threshold intensities, y={y_(i):         I_(LL)<I_(i)<I_(UL)}     -   III. Sort y in increasing order to obtain y*.     -   IV. Calculate d={d₁, d₂, . . . , d_(m)}, where         d_(i)=y_(i+1)*−y_(i)*.     -   V. Calculate a gap statistic for each of the observed         intensities:

$x_{j} = \frac{\sum\limits_{i = {j - w}}^{j + w}d_{i}}{{2w} + 1}$

-   -   VI. Identify the threshold c, such that c=max(x_(j))     -   VII. Count the number of spots, k, above the threshold c, where         k=Σ_(i=1) ^(m)I[y_(i)>c].     -   VIII. Given a number of simulations desired, nsim, perform the         following procedure nsim times: Randomly select m values with         replacement from y={y₁, y₂, . . . , y_(m)} to obtain y_(sim).         Then repeat Step I-VII with y_(sim) to obtain a final count.     -   IX. Calculate {circumflex over (σ)}_(k) the standard deviation         of the nsim simulated counts.     -   X. Calculate the 95% CI for the count as:

[k−1.96{circumflex over (σ)}_(k)+1.96{circumflex over (σ)}_(k)]

-   -   -   Note that in order to obtain the true estimate of the             molecule count in the sample, we needed to transform by:

$N = {{- m}*{\log\left( {1 - \frac{k}{m}} \right)}}$

-   -   -   and similarly, for the 95% CI upper and lower values, where             m is the total number of features on the array.

Example 6—Detection of Kan Genes

The purpose of this experiment was to determine the count of kan genes in a sample. The sample containing the kan genes was hybridized to an array. FIG. 4A displays a region of the array acquired from the imaging system. The bright intensity at a spot was correlated with a higher probability of a gene being present at the spot. The image analysis software examined the statistics of the intensity distribution, such as deviance, skewness, kurtosis, and median. These statistics provided guidance for the software to automatically choose the best method to detect the presence of kan genes. In this example, a mixture model algorithm was used to determine the intensity threshold to be 6.6, which optimally divided the intensity distribution into “on” and “off” domains, as shown in FIG. 4B.

Example 7—Titration Experiment

The purpose of this experiment was to detect the presence of molecular hybridization in a titration experiment. After obtaining the intensity measurements of a region, the intensity distribution was computed and is shown in FIG. 5. A person with ordinary skill can identify two modes in the distribution; however, it was very difficult to determine the precise value of the threshold. The invented software automated the task of determining the signal intensity threshold, and determined that an intensity value of 6.02 provides the optimal threshold for distinguishing between labeled and non-labeled features.

Example 8—Background Adjustment

The purpose of this experiment was to demonstrate use of one background subtraction method to process images. FIG. 6A shows an acquired image with pronounced artifacts. A systematic background subtraction was performed to reduce noise. We defined an analysis window centered on a spot. The software then calculated the mean spot intensity, S, spot standard deviation {circumflex over (σ)}_(S), number of spot pixels n_(S), background mean B, background standard deviation σ_(B), and number of background pixels n_(B). Then, the software calculated the log 2 background subtracted intensity statistic for each spot:

$I = {\frac{{\log_{2}\left( {16\overset{\_}{S}} \right)} - {\log_{2}\left( {16\overset{\_}{B}} \right)}}{\sqrt{\frac{\tau_{S}^{2}}{n_{S}} + \frac{\tau_{B}^{2}}{n_{B}}}}\mspace{14mu} {where}}$ $\begin{matrix} {\tau_{S} = {{\log_{2}\left( {16\left( {\sigma_{S} + \overset{\_}{S}} \right)} \right)} - {\log_{2}\left( {16\sigma_{S}} \right)}}} \\ {\tau_{B} = {{\log_{2}\left( {16\left( {\sigma_{B} + \overset{\_}{B}} \right)} \right)} - {{\log_{2}\left( {16\sigma_{B}} \right)}.}}} \end{matrix}$

FIGS. 6B and 6C show the intensity distributions before and after background adjustment, respectively, demonstrating that background correction enhances the ability of the software to correctly evaluate the presence of the labeled features on the array.

Example 9—Alternative Background Correction

The purpose of this experiment was an alternative way to adjust background. We defined an analysis window centered on a spot. The software then calculated the median spot intensity S and median local background intensity B. Then, the software calculated the log 2 background subtracted intensity statistic for each spot:

I=log₂(16{tilde over (S)})−log₂(16{tilde over (S)}).

Example 10—Pixel16 Cartridge and Custom Microarray

This example illustrated one embodiment of an array for use with the disclosed methods, systems, and platforms in performing stochastic labeling experiment.

The Pixel16 cartridge consists of (i) an epoxysilane functionalized glass slide serving as an array substrate, (ii) 16 copies of the custom microarray described in FIGS. 14-16, printed on the functionalized surface of the slide, and (iii) a polymer well frame affixed to the printed side of the slide which serves to define 16 wells which are fluidically separate and in register with the array pattern. The well frame is affixed to the slide following array printing using a die-cut double-sided adhesive.

Custom DNA microarray layout. The microarray pattern consists of a 32×32 array of spots as shown in FIGS. 15 and 16. Fiducial spots in the top and bottom rows permit location of the array in the scanned images. Also, the fiducial spots are arranged in an asymmetric pattern whose orientation is readily identifiable: the top row has a distinctive pattern whose ends are distinct, and the bottom row is different from the top row. This permits easy manual and automatic identification of incorrect placement of the Pixel16, and also facilitates detection of imaging problems. The remaining 960 spots are each associated with one of the unique probe sequences listed in Table 1.

Oligonucleotide sequences and solution components. Oligonucleotide solutions are provided for preparation of printing solutions in 96-well microplates. Concentration as supplied is 100 μM in H2O. Dilution prior to printing is performed using the Tecan GenMate. Dilution is 880 μL of stock oligo+1320 μL of buffer. The dilution buffer used is 250 mM sodium phosphate with 0.00833% sarcosyl. Buffer is filtered using a 0.2 μm filter. Three sets of plates are prepared in each probe preparation operation. Tips are discarded after each source plate. The final dispensed solution is 40 μM DNA in 150 mM sodium phosphate with 0.005% sarcosyl. The fiducial oligo is supplied at 500 μM in H2O. The fiducial oligonucleotide sequence is: 5′-/5AmMC6/TCC TGA ACG GTA GCATCT TGA CGA C -3′ (Seq ID No: 1), 25 bases, 5′ Amino Modifier C6, standard desalting; supplied at 500 μM in H2O. The fiducial is diluted by mixing 176 μL of fiducial, 704 μL of water, and 1320 μL of buffer. The final fiducial mixture is 40 μM in 150 mM sodium phosphate with 0.005% sarcosyl.

Table of oligonucleotide sequences. The oligonucleotide sequences for the 960 probe sequences (i.e. the sequences that are complementary to the set of stochastic labeling sequences used in molecular counting experiments) are listed in Table 1.

TABLE 1 Oligonucleotide Probe Sequences for Custom Microarray IDT IDT Calc'd Seq Plate Ref. Well Seq Mfg Molec. ID Name # Pos. Name Sequence ID Weight T_(m) No AJ_P1 85652 A01 AJ_1 /5AmMC6/CCC AAA GGG TAC 10653 8795 61.7   2   789 CAG AGC TTA AGG TCA A  4039 AJ_P1 85652 A02 AJ_2 /5AmMC6/CCC AAA GCG TTA 10653 8727 59.7   3   790 AGG TTT CTT GTC ACA A  4040 AJ_P1 85652 A03 AJ_3 /5AmMC6/CCC AAG TCG TAC 10653 8675 61.8   4   791 GAA CTC ACC ACA TGA A  4041 AJ_P1 85652 A04 AJ_4 /5AmMC6/CCC AAA CTT GTT 10653 8672 60.3   5   792 CCC TTG AGA CCA GTA A  4042 AJ_P1 85652 A05 AJ_5 /5AmMC6/CCC AAG ACT TCT 10653 8657 60.7   6   793 ACC CTA GGT TCC AGA A  4043 AJ_P1 85652 A06 AJ_6 /5AmMC6/CCC AAC CAG ACT 10653 8755 62.3   7   794 TGG GTA CGT GAA ACA A  4044 AJ_P1 85652 A07 AJ_7 /5AmMC6/CCC AAC GAC TGG 10653 8786 62.3   8   795 TTC TGA AGT GGA ACA A  4045 AJ_P1 85652 A08 AJ_8 /5AmMC6/CCC AAT TTA GCT 10653 8712 60.4   9   796 TCG TGA GTC AGA CCA A  4046 AJ_P1 85652 A09 AJ_9 /5AmMC6/CCC AAC TCG AAG 10653 8752 59.8  10   797 AGT GGT CAG TCT TTA A  4047 AJ_P1 85652 A10 AJ_10 /5AmMC6/CCC AAT CGC AAG 10653 8745 58.4  11   798 GAG ACA TAG TCT TTA A  4048 AJ_P1 85652 A11 AJ_11 /5AmMC6/CCC AAG TCC TAG 10653 8761 60  12   799 TGA GAG CAA CGT TTA A  4049 AJ_P1 85652 A12 AJ_12 /5AmMC6/CCC AAG GAA CCT 10653 8697 61.4  13   800 ACT GTC CTT GTC AGA A  4050 AJ_P1 85652 B01 AJ_13 /5AmMC6/CCC AAA CTA GAA 10653 8779 59.7  14   801 GAC GAG TTC GAG TCA A  4051 AJ_P1 85652 B02 AJ_14 /5AmMC6/CCC AAG GAC ATA 10653 8699 60  15   802 CTC AAC GTA GCT CAA A  4052 AJ_P1 85652 B03 AJ_15 /5AmMC6/CCC AAG GCA TTT 10653 8690 61.9  16   803 GCA ACC TCA CAT GAA A  4053 AJ_P1 85652 B04 AJ_16 /5AmMC6/CCC AAG TAC CCA 10653 8666 61.3  17   804 TCC ACT GTC GAG TAA A  4054 AJ_P1 85652 B05 AJ_17 /5AmMC6/CCC AAA GCG TTT 10653 8745 59.4  18   805 GTG TAA CAG ACC ATA A  4055 AJ_P1 85652 B06 AJ_18 /5AmMC6/CCC AAA TGG TCT 10653 8737 62.3  19   806 GGT TCG ACA GTC ACA A  4056 AJ_P1 85652 B07 AJ_19 /5AmMC6/CCC AAG AGG TAC 10653 8795 60.6  20   807 AAC GAC TCT AGG GTA A  4057 AJ_P1 85652 B08 AJ_20 /5AmMC6/CCC AAG AAC TTC 10653 8687 58.9  21   808 TAC TTG CTT CGT GAA A  4058 AJ_P1 85652 B09 AJ_21 /5AmMC6/CCC AAG CAC TTT 10653 8687 58.8  22   809 CTG TTA ACT AGC TGA A  4059 AJ_P1 85652 B10 AJ_22 /5AmMC6/CCC AAG AAC CTC 10653 8672 58.6  23   810 TCT CTA GTG CTA GTA A  4060 AJ_P1 85652 B11 AJ_23 /5AmMC6/CCC AAG CCT TTA 10653 8681 60.4  24   811 AGC CTA AAG TCC TGA A  4061 AJ_P1 85652 B12 AJ_24 /5AmMC6/CCC AAT CTG GTA 10653 8672 60.3  25   812 GCT CAA CAT CCT TGA A  4062 AJ_P1 85652 C01 AJ_25 /5AmMC6/CCC AAA GGA CTC 10653 8795 61.8  26   813 CAT GGA GAA GTG TCA A  4063 AJ_P1 85652 C02 AJ_26 /5AmMC6/CCC AAG AAC CCT 10653 8657 62.4  27   814 TTC TGG AAG CTT CCA A  4064 AJ_P1 85652 C03 AJ_27 /5AmMC6/CCC AAA TTC GCT 10653 8712 60.1  28   815 TCC TAG TAG TGG ACA A  4065 AJ_P1 85652 C04 AJ_28 /5AmMC6/CCC AAC CGT ACG 10653 8681 59.4  29   816 AAG ACC TAG TTT CTA A  4066 AJ_P1 85652 C05 AJ_29 /5AmMC6/CCC AAT CAC GAA 10653 8745 58.4  30   817 GAG AGT CAC TGT TTA A  4067 AJ_P1 85652 C06 AJ_30 /5AmMC6/CCC AAG AAA CAT 10653 8763 59.3  31   818 AAA CTC GAG TTG CGA A  4068 AJ_P1 85652 C07 AJ_31 /5AmMC6/CCC AAC CAG TTA 10653 8752 60.7  32   819 CGT GAG TGT TGC TAA A  4069 AJ_P1 85652 C08 AJ_32 /5AmMC6/CCC AAA CTC GTG 10653 8672 60.5  33   820 ACT CCT GTT TCA GAA A  4070 AJ_P1 85652 C09 AJ_33 /5AmMC6/CCC AAC GGT TGA 10653 8779 60.6  34   821 AGA GAC TCC TGA AAA A  4071 AJ_P1 85652 C10 AJ_34 /5AmMC6/CCC AAA TTG CTC 10653 8705 59.8  35   822 TGG TCA CAT CGA AAA A  4072 AJ_P1 85652 C11 AJ_35 /5AmMC6/CCC AAC AGG ACT 10653 8752 60.7  36   823 TGT GCT ACG TGT TAA A  4073 AJ_P1 85652 C12 AJ_36 /5AmMC6/CCC AAA TTT CGT 10653 8672 61.9  37   824 GTG TCA ACC ATG CCA A  4074 AJ_P1 85652 D01 AJ_37 /5AmMC6/CCC AAC GTG AAG 10653 8754 59.7  38   825 GCT TAA CAA CAT TGA A  4075 AJ_P1 85652 D02 AJ_38 /5AmMC6/CCC AAT GAA CAC 10653 8723 59  39   826 AAC TAC GAA GCT GTA A  4076 AJ_P1 85652 D03 AJ_39 /5AmMC6/CCC AAA CTT CCG 10653 8687 58.7  40   827 TTG TTA CTA GTC GAA A  4077 AJ_P1 85652 D04 AJ_40 /5AmMC6/CCC AAG GAG TAC 10653 8786 61  41   828 AAG CTT CCT AGG GTA A  4078 AJ_P1 85652 D05 AJ_41 /5AmMC6/CCC AAG TGC TAA 10653 8687 58.8  42   829 ACT GCT CTT TAC GTA A  4079 AJ_P1 85652 D06 AJ_42 /5AmMC6/CCC AAA GAA ACT 10653 8705 59.5  43   830 GCA TCT CCT TTG GAA A  4080 AJ_P1 85652 D07 AJ_43 /5AmMC6/CCC AAG GAC TAA 10653 8666 61.4  44   831 GTT CCA CTC ACC TGA A  4081 AJ_P1 85652 D08 AJ_44 /5AmMC6/CCC AAA GTT GTC 10653 8752 60.5  45   832 TGG TTC ACT CGA GAA A  4082 AJ_P1 85652 D09 AJ_45 /5AmMC6/CCC AAC GTT CTA 10653 8727 59.2  46   833 AGT TTG CTT CGA AGA A  4083 AJ_P1 85652 D10 AJ_46 /5AmMC6/CCC AAC TAA AGG 10653 8730 61.5  47   834 TTG TGC ATC CAA GCA A  4084 AJ_P1 85652 D11 AJ_47 /5AmMC6/CCC AAA GGC TTC 10653 8696 59.4  48   835 ACG ACA TGT CAT TTA A  4085 AJ_P1 85652 D12 AJ_48 /5AmMC6/CCC AAC TGC TAG 10653 8681 59.7  49   836 GTT CCT ACA CAA GTA A  4086 AJ_P1 85652 E01 AJ_49 /5AmMC6/CCC AAA TCA GTA 10653 8699 59.8  50   837 GCT ACA CCA CAG GTA A  4087 AJ_P1 85652 E02 AJ_50 /5AmMC6/CCC AAG ACT GCA 10653 8690 60.6  51   838 AGC TCA CTA CAT TGA A  4088 AJ_P1 85652 E03 AJ_51 /5AmMC6/CCC AAG CTA CTC 10653 8690 58.9  52   839 CTC TAA GAG CAT AGA A  4089 AJ_P1 85652 E04 AJ_52 /5AmMC6/CCC AAT GGA ACG 10653 8779 60.9  53   840 CTA AGG TGT AAA CCA A  4090 AJ_P1 85652 E05 AJ_53 /5AmMC6/CCC AAG AAA CTA 10653 8690 61.5  54   841 ACC TTG GCT TGC CAA A  4091 AJ_P1 85652 E06 AJ_54 /5AmMC6/CCC AAC CAT TAG 10653 8672 61.3  55   842 ACC TTG TGT TGC CAA A  4092 AJ_P1 85652 E07 AJ_55 /5AmMC6/CCC AAG GTC TGA 10653 8777 61.7  56   843 CAG TAG GTG TTC CAA A  4093 AJ_P1 85652 E08 AJ_56 /5AmMC6/CCC AAT TTC GCA 10653 8696 59.7  57   844 AGC CTT GGT ACA TAA A  4094 AJ_P1 85652 E09 AJ_57 /5AmMC6/CCC AAG TTT CTA 10653 8657 61.2  58   845 GCC TAC CAC TAC GGA A  4095 AJ_P1 85652 E10 AJ_58 /5AmMC6/CCC AAA TAG ACC 10653 8779 60.1  59   846 TAA CGG AAG CTG TGA A  4096 AJ_P1 85652 E11 AJ_59 /5AmMC6/CCC AAG GAG TCA 10653 8712 60.7  60   847 TCC ATG CAT CTT TGA A  4097 AJ_P1 85652 E12 AJ_60 /5AmMC6/CCC AAC CGT ACT 10653 8721 60.5  61   848 AGC TTG GGT TAA ACA A  4098 AJ_P1 85652 F01 AJ_61 /5AmMC6/CCC AAA AAG GCT 10653 8696 59  62   849 AGC CTT CTG ACT TTA A  4099 AJ_P1 85652 F02 AJ_62 /5AmMC6/CCC AAA GAG CTC 10653 8705 58.8  63   850 TGC ACT ACA AGT TTA A  4100 AJ_P1 85652 F03 AJ_63 /5AmMC6/CCC AAC AGC TAA 10653 8779 60  64   851 CGG TAG TAA AGG TCA A  4101 AJ_P1 85652 F04 AJ_64 /5AmMC6/CCC AAA GCT TTC 10653 8696 60  65   852 CGT TTC AAA GTG ACA A  4102 AJ_P1 85652 F05 AJ_65 /5AmMC6/CCC AAG TCC ATG 10653 8690 61.3  66   853 CTT CCA GTG ACA AAA A  4103 AJ_P1 85652 F06 AJ_66 /5AmMC6/CCC AAG TAG CTT 10653 8687 58.4  67   854 TGC TCT ACT CGT AAA A  4104 AJ_P1 85652 F07 AJ_67 /5AmMC6/CCC AAC TTC GAA 10653 8779 59.7  68   855 CTA AGG AGT AGA GCA A  4105 AJ_P1 85652 F08 AJ_68 /5AmMC6/CCC AAT TCA GTC 10653 8770 58.5  69   856 CTA GAG GAG AGA CTA A  4106 AJ_P1 85652 F09 AJ_69 /5AmMC6/CCC AAT AGG TCT 10653 8672 59.6  70   857 GTC TTA CCC AAC GTA A  4107 AJ_P1 85652 F10 AJ_70 /5AmMC6/CCC AAC GTG AGG 10653 8770 60.7  71   858 AAA GTT CTG CTA ACA A  4108 AJ_P1 85652 F11 AJ_71 /5AmMC6/CCC AAG TTG GCA 10653 8712 60.7  72   859 ACT TGC TCT CTA AGA A  4109 AJ_P1 85652 F12 AJ_72 /5AmMC6/CCC AAG ACA TCT 10653 8690 59  73   860 CTC TCA GAG CTA GAA A  4110 AJ_P1 85652 G01 AJ_73 /5AmMC6/CCC AAT TTC GCA 10653 8672 60.9  74   861 TGT CTC ATC AGG ACA A  4111 AJ_P1 85652 G02 AJ_74 /5AmMC6/CCC AAA GCC TTC 10653 8721 60.6  75   862 CTT GGT ACT GAA AGA A  4112 AJ_P1 85652 G03 AJ_75 /5AmMC6/CCC AAA CTT GCC 10653 8696 59.9  76   863 TTG CGT ACT GTA AAA A  4113 AJ_P1 85652 G04 AJ_76 /5AmMC6/CCC AAC ACT TTG 10653 8761 59.7  77   864 TAC GGT AGA GAC GTA A  4114 AJ_P1 85652 G05 AJ_77 /5AmMC6/CCC AAG TTT CCA 10653 8681 61.2  78   865 TCA ACC GAA GCT TGA A  4115 AJ_P1 85652 G06 AJ_78 /5AmMC6/CCC AAG CAT TAC 10653 8699 61  79   866 CAA ACT GGA ACC TGA A  4116 AJ_P1 85652 G07 AJ_79 /5AmMC6/CCC AAC CGT ACA 10653 8687 59.7  80   867 ACT TGT TCG TTT GAA A  4117 AJ_P1 85652 G08 AJ_80 /5AmMC6/CCC AAC AGC TAG 10653 8690 60.7  81   868 TAG CAC ACC ATT TGA A  4118 AJ_P1 85652 G09 AJ_81 /5AmMC6/CCC AAC CTC ACG 10653 8690 61.2  82   869 AAA GCA TCA TTG TGA A  4119 AJ_P1 85652 G10 AJ_82 /5AmMC6/CCC AAA CAA AGT 10653 8739 60.5  83   870 GAG GTC ATC TCG ACA A  4120 AJ_P1 85652 G11 AJ_83 /5AmMC6/CCC AAG AAA CCT 10653 8721 59.9  84   871 TCT TGT AGG ACT CGA A  4121 AJ_P1 85652 G12 AJ_84 /5AmMC6/CCC AAA AGC CTA 10653 8696 58.9  85   872 AGC TCT GTC AGT TTA A  4122 AJ_P1 85652 H01 AJ_85 /5AmMC6/CCC AAA CGT TCC 10653 8681 60.9  86   873 CTT CAT GTC GAA AGA A  4123 AJ_P1 85652 H02 AJ_86 /5AmMC6/CCC AAG TAG CAC 10653 8699 60.7  87   874 TGA CAC CAA GCA TTA A  4124 AJ_P1 85652 H03 AJ_87 /5AmMC6/CCC AAG TTT GAC 10653 8657 62.2  88   875 TCC AAG CCT ACG TCA A  4125 AJ_P1 85652 H04 AJ_88 /5AmMC6/CCC AAA CCG TTG 10653 8770 61.2  89   876 GTG AAG CCT TAA AGA A  4126 AJ_P1 85652 H05 AJ_89 /5AmMC6/CCC AAG CCT ACA 10653 8675 61.9  90   877 CCT TCA GTG AAC AGA A  4127 AJ_P1 85652 H06 AJ_90 /5AmMC6/CCC AAC AGC TCA 10653 8723 59.2  91   878 AGC AGT TAG TAA ACA A  4128 AJ_P1 85652 H07 AJ_91 /5AmMC6/CCC AAT ACG CAA 10653 8745 59.3  92   879 GCA TGT AGG TTT ACA A  4129 AJ_P1 85652 H08 AJ_92 /5AmMC6/CCC AAC ACG AGT 10653 8727 59.3  93   880 CGT TAG TTG TTT CAA A  4130 AJ_P1 85652 H09 AJ_93 /5AmMC6/CCC AAT TCG GAA 10653 8690 59.6  94   881 GAC CTA CTA ACC TGA A  4131 AJ_P1 85652 H10 AJ_94 /5AmMC6/CCC AAA GGT CTC 10653 8763 58.2  95   882 TAC GAA AGG AAC ATA A  4132 AJ_P1 85652 H11 AJ_95 /5AmMC6/CCC AAG TGC TAG 10653 8761 60.6  96   883 ACG TCT GTG TCA AAA A  4133 AJ_P1 85652 H12 AJ_96 /5AmMC6/CCC AAA CCA GTG 10653 8657 61  97   884 GAC TTC TCT CCT AGA A  4134 AJ_P2 85652 A01 AJ_97 /5AmMC6/CCC AAC ATG TAG 10653 8746 61.3  98   886 GAG ACG TAG TTC CCA A  4135 AJ_P2 85652 A02 AJ_98 /5AmMC6/CCC AAG AAC TCT 10653 8752 60.2  99   887 CTG GTT AGG CTT GAA A  4136 AJ_P2 85652 A03 AJ_99 /5AmMC6/CCC AAG GAC ATC 10653 8675 62.1 100   888 CAC ATC GTC TGA CAA A  4137 AJ_P2 85652 A04 AJ_100 /5AmMC6/CCC AAA CTT GTT 10653 8736 59.8 101   889 GGG TTC AGC TAA CAA A  4138 AJ_P2 85652 A05 AJ_101 /5AmMC6/CCC AAC ACG TGT 10653 8681 61.2 102   890 CCT GTC ATG TCA AAA A  4139 AJ_P2 85652 A06 AJ_102 /5AmMC6/CCC AAT CGG AAA 10653 8705 59.4 103   891 CCA ACG TTA GCT TTA A  4140 AJ_P2 85652 A07 AJ_103 /5AmMC6/CCC AAG GAC TTA 10653 8777 61.4 104   892 GGT ACC TGT TCG GAA A  4141 AJ_P2 85652 A08 AJ_104 /5AmMC6/CCC AAG ACT TAA 10653 8739 60.1 105   893 CAA CCT GTG ACG AGA A  4142 AJ_P2 85652 A09 AJ_105 /5AmMC6/CCC AAG TTA ACA 10653 8779 60.7 106   894 TGC AGA CGA ACG GTA A  4143 AJ_P2 85652 A10 AJ_106 /5AmMC6/CCC AAG CGT ACA 10653 8687 58.9 107   895 ACT CTT GTC AGT TTA A  4144 AJ_P2 85652 A11 AJ_107 /5AmMC6/CCC AAG TAA CAC 10653 8746 61.9 108   896 CTT CTG AGC AGT GGA A  4145 AJ_P2 85652 A12 AJ_108 /5AmMC6/CCC AAG ACC TAC 10653 8675 60.7 109   897 CTC TCA GGA ACA GTA A  4146 AJ_P2 85652 B01 AJ_109 /5AmMC6/CCC AAA CCT GAC 10653 8739 59.9 110   898 CTT AGG AAG AGC ATA A  4147 AJ_P2 85652 B02 AJ_110 /5AmMC6/CCC AAC AAA GTT 10653 8736 59.3 111   899 TGT CTC AGT TAG CGA A  4148 AJ_P2 85652 B03 AJ_111 /5AmMC6/CCC AAC GGT AGC 10653 8752 60.5 112   900 ATT GTT CCT GTA GAA A  4149 AJ_P2 85652 B04 AJ_112 /5AmMC6/CCC AAC TAG GTT 10653 8727 58 113   901 TGT TCT AGA CAG CTA A  4150 AJ_P2 85652 B05 AJ_113 /5AmMC6/CCC AAG TCT CTA 10653 8681 59.8 114   902 CGT TCC ATC GAA AGA A  4151 AJ_P2 85652 B06 AJ_114 /5AmMC6/CCC AAA CCT TCG 10653 8672 60.7 115   903 TTC TTG AGT ACA GCA A  4152 AJ_P2 85652 B07 AJ_115 /5AmMC6/CCC AAG AAC ACT 10653 8666 62.2 116   904 CCT CAT GTG ACT GCA A  4153 AJ_P2 85652 B08 AJ_116 /5AmMC6/CCC AAA CGC TTG 10653 8763 59.3 117   905 GTA ACA AAG ACA GTA A  4154 AJ_P2 85652 B09 AJ_117 /5AmMC6/CCC AAC CCT AGA 10653 8721 58.4 118   906 GTA GTA CTA CGG TTA A  4155 AJ_P2 85652 B10 AJ_118 /5AmMC6/CCC AAC CTG AGG 10653 8779 60.3 119   907 TAG TGA CTG AAA CAA A  4156 AJ_P2 85652 B11 AJ_119 /5AmMC6/CCC AAG CTA CGA 10653 8727 59.7 120   908 ACT TGG TTG TTT CAA A  4157 AJ_P2 85652 B12 AJ_120 /5AmMC6/CCC AAG CAA GTC 10653 8752 60.8 121   909 CTA GGT TGT GTT CAA A  4158 AJ_P2 85652 C01 AJ_121 /5AmMC6/CCC AAC TCC ATG 10653 8755 61.9 122   910 TCA AGG AAG GGT ACA A  4159 AJ_P2 85652 C02 AJ_122 /5AmMC6/CCC AAT CCG AAC 10653 8723 58.7 123   911 ACG AAG TAC AAG TTA A  4160 AJ_P2 85652 C03 AJ_123 /5AmMC6/CCC AAC ACG TTG 10653 8727 60.1 124   912 ACA TTG TTG GCT TAA A  4161 AJ_P2 85652 C04 AJ_124 /5AmMC6/CCC AAC CTC TAG 10653 8675 60.9 125   913 GAA CGT AGT ACA CCA A  4162 AJ_P2 85652 C05 AJ_125 /5AmMC6/CCC AAT AGG ACA 10653 8699 60.3 126   914 CCA CAG TTC ATC GAA A  4163 AJ_P2 85652 C06 AJ_126 /5AmMC6/CCC AAA TGT CGT 10653 8736 59.7 127   915 TCG GTT AGC TCA AAA A  4164 AJ_P2 85652 C07 AJ_127 /5AmMC6/CCC AAA TCG GTT 10653 8736 59.4 128   916 GTG TCT AGC TCA AAA A  4165 AJ_P2 85652 C08 AJ_128 /5AmMC6/CCC AAT AAG AAC 10653 8723 59.3 129   917 GAA ACG TAC CTT GCA A  4166 AJ_P2 85652 C09 AJ_129 /5AmMC6/CCC AAT CGC AAG 10653 8723 59.7 130   918 AAC CGT TAG TCA AAA A  4167 AJ_P2 85652 C10 AJ_130 /5AmMC6/CCC AAG TCA CAC 10653 8657 61.9 131   919 GTC TCC ACA GGT TTA A  4168 AJ_P2 85652 C11 AJ_131 /5AmMC6/CCC AAG AGC TTA 10653 8752 59.4 132   920 CAT CGT TCT AGG GTA A  4169 AJ_P2 85652 C12 AJ_132 /5AmMC6/CCC AAG ACC TTC 10653 8697 61 133   921 TCC TTG ACA GAG GTA A  4170 AJ_P2 85652 D01 AJ_133 /5AmMC6/CCC AAA AGG CTT 10653 8687 58.6 134   922 AGC TCT CTT TAC TGA A  4171 AJ_P2 85652 D02 AJ_134 /5AmMC6/CCC AAG TCG TAA 10653 8755 61.9 135   923 CAG AGG TGT CCA CAA A  4172 AJ_P2 85652 D03 AJ_135 /5AmMC6/CCC AAA CTA CTG 10653 8761 60.5 136   924 CAA GTG GTA GGT TCA A  4173 AJ_P2 85652 D04 AJ_136 /5AmMC6/CCC AAT TTC GGA 10653 8746 62.3 137   925 ACC AGT ACC ATG GGA A  4174 AJ_P2 85652 D05 AJ_137 /5AmMC6/CCC AAT CGA GAA 10653 8705 59.1 138   926 GCA ACT TCC TTG TAA A  4175 AJ_P2 85652 D06 AJ_138 /5AmMC6/CCC AAT GGA GAC 10653 8752 60.3 139   927 TTC CGT ACT GTT GAA A  4176 AJ_P2 85652 D07 AJ_139 /5AmMC6/CCC AAA CAT GCG 10653 8687 59.6 140   928 TTT CGT AGT CTT CAA A  4177 AJ_P2 85652 D08 AJ_140 /5AmMC6/CCC AAG AAC CTC 10653 8690 60.4 141   929 AGC TCT TTC GAA AGA A  4178 AJ_P2 85652 D09 AJ_141 /5AmMC6/CCC AAG TCC TTA 10653 8752 59.7 142   930 AGC TGT TCG AGA GTA A  4179 AJ_P2 85652 D10 AJ_142 /5AmMC6/CCC AAT CTC GAA 10653 8672 60.5 143   931 ACT CTT GTG TGA CCA A  4180 AJ_P2 85652 D11 AJ_143 /5AmMC6/CCC AAC CAT TAG 10653 8763 57.7 144   932 AGG AAC TAA GAG CTA A  4181 AJ_P2 85652 D12 AJ_144 /5AmMC6/CCC AAC CCT AGA 10653 8755 60.7 145   933 GTG AGT CAG GAA CTA A  4182 AJ_P2 85652 E01 AJ_145 /5AmMC6/CCC AAT GAA CCA 10653 8763 59.1 146   934 TAA GAG CAA CGG TTA A  4183 AJ_P2 85652 E02 AJ_146 /5AmMC6/CCC AAG AAC CTT 10653 8672 60.3 147   935 CCC TTA GTC GTT GAA A  4184 AJ_P2 85652 E03 AJ_147 /5AmMC6/CCC AAG TGG TCA 10653 8697 62.1 148   936 GTA ACC CTT TCC GAA A  4185 AJ_P2 85652 E04 AJ_148 /5AmMC6/CCC AAA GCA TGT 10653 8681 59.3 149   937 ACG TCT CCT ACT AGA A  4186 AJ_P2 85652 E05 AJ_149 /5AmMC6/CCC AAG GAC TTC 10653 8666 61.9 150   938 ACC TAC GTT CGA ACA A  4187 AJ_P2 85652 E06 AJ_150 /5AmMC6/CCC AAC GAA CTT 10653 8672 60.7 151   939 TAC CTT GTC CAT GGA A  4188 AJ_P2 85652 E07 AJ_151 /5AmMC6/CCC AAC AGG TTC 10653 8690 61.1 152   940 TTA CGC AAC ACA TGA A  4189 AJ_P2 85652 E08 AJ_152 /5AmMC6/CCC AAC TTG TTA 10653 8752 60.1 153   941 GGG TAG CTG ACT CAA A  4190 AJ_P2 85652 E09 AJ_153 /5AmMC6/CCC AAC TGG AGA 10653 8770 59.2 154   942 AGA GAC TAC CTG TTA A  4191 AJ_P2 85652 E10 AJ_154 /5AmMC6/CCC AAC TAA GGT 10653 8752 60.3 155   943 TTG GTC AGT CCT GAA A  4192 AJ_P2 85652 E11 AJ_155 /5AmMC6/CCC AAG CAC ACT 10653 8690 60.7 156   944 AGC CTT TCT GAA AGA A  4193 AJ_P2 85652 E12 AJ_156 /5AmMC6/CCC AAG TCC TGA 10653 8777 61.6 157   945 CGA GAG TTT GGT ACA A  4194 AJ_P2 85652 F01 AJ_157 /5AmMC6/CCC AAT CCC AAG 10653 8697 61.8 158   946 AGT CTC TGG TTG ACA A  4195 AJ_P2 85652 F02 AJ_158 /5AmMC6/CCC AAG GCA TTC 10653 8687 59.8 159   947 AGC ATT CAT TCT TGA A  4196 AJ_P2 85652 F03 AJ_159 /5AmMC6/CCC AAG TTT GAC 10653 8690 61.3 160   948 TAC CAA GCA ACT GCA A  4197 AJ_P2 85652 F04 AJ_160 /5AmMC6/CCC AAC CTT AAG 10653 8770 60 161   949 CTA AGT GTG AGA CGA A  4198 AJ_P2 85652 F05 AJ_161 /5AmMC6/CCC AAC TTA CAG 10653 8736 59.2 162   950 CTA GTT TGA AGT GCA A  4199 AJ_P2 85652 F06 AJ_162 /5AmMC6/CCC AAC TAG TCT 10653 8727 58.3 163   951 CTT AGA GTT TGG CAA A  4200 AJ_P2 85652 F07 AJ_163 /5AmMC6/CCC AAT AAA GCT 10653 8763 58 164   952 CTA GGA GAA CAC GTA A  4201 AJ_P2 85652 F08 AJ_164 /5AmMC6/CCC AAA GCG TAG 10653 8779 59.8 165   953 TAG TGA CTA ACG ACA A  4202 AJ_P2 85652 F09 AJ_165 /5AmMC6/CCC AAG ACG TAA 10653 8681 59.9 166   954 ACG CTT CCT TCT AGA A  4203 AJ_P2 85652 F10 AJ_166 /5AmMC6/CCC AAA GCT GTA 10653 8672 59.5 167   955 GTA CCC TTT CCT AGA A  4204 AJ_P2 85652 F11 AJ_167 /5AmMC6/CCC AAC TCG TAC 10653 8699 59.3 168   956 AGC ATA CCT AGA AGA A  4205 AJ_P2 85652 F12 AJ_168 /5AmMC6/CCC AAT CGC TAC 10653 8723 58.9 169   957 ATA GCA ACT GAA AGA A  4206 AJ_P2 85652 G01 AJ_169 /5AmMC6/CCC AAC TTG GCA 10653 8761 61 170   958 ACG TGT GTA GTA CAA A  4207 AJ_P2 85652 G02 AJ_170 /5AmMC6/CCC AAA CCT GTT 10653 8696 59.9 171   959 ACG CTT GTG CTA AAA A  4208 AJ_P2 85652 G03 AJ_171 /5AmMC6/CCC AAA GCT TGG 10653 8727 59.4 172   960 TTG TAA CTT TAC CGA A  4209 AJ_P2 85652 G04 AJ_172 /5AmMC6/CCC AAG AGA CCT 10653 8699 60.5 173   961 TAG CAA CAA CCT TGA A  4210 AJ_P2 85652 G05 AJ_173 /5AmMC6/CCC AAT ACC GAA 10653 8761 60.1 174   962 GAG TGC TAG GTT TCA A  4211 AJ_P2 85652 G06 AJ_174 /5AmMC6/CCC AAG ACA TAG 10653 8666 61.6 175   963 TAC CGT TGC TAC CCA A  4212 AJ_P2 85652 G07 AJ_175 /5AmMC6/CCC AAG GTC TAG 10653 8739 59.7 176   964 TAA CGA AGC AAC CTA A  4213 AJ_P2 85652 G08 AJ_176 /5AmMC6/CCC AAT AAG CAA 10653 8723 60.1 177   965 CAA AGG TCA TTG CCA A  4214 AJ_P2 85652 G09 AJ_177 /5AmMC6/CCC AAC TGA GTG 10653 8779 59.5 178   966 AGA AGT CAG AAC CTA A  4215 AJ_P2 85652 G10 AJ_178 /5AmMC6/CCC AAC TTC GAG 10653 8723 58.8 179   967 TGA AAC AAG AAC CTA A  4216 AJ_P2 85652 G11 AJ_179 /5AmMC6/CCC AAA GCG TTC 10653 8727 59.4 180   968 ATG GTT CTG TCA TAA A  4217 AJ_P2 85652 G12 AJ_180 /5AmMC6/CCC AAG AGG TCT 10653 8752 59.7 181   969 AGG CTT TCG TCT AAA A  4218 AJ_P2 85652 H01 AJ_181 /5AmMC6/CCC AAA GCC ATT 10653 8712 60.7 182   970 AGT CGT GTC GTT ACA A  4219 AJ_P2 85652 H02 AJ_182 /5AmMC6/CCC AAG GTC TTA 10653 8777 61.9 183   971 CGT AGG TTG AAG CCA A  4220 AJ_P2 85652 H03 AJ_183 /5AmMC6/CCC AAG AGC TTA 10653 8739 60.2 184   972 GCG AAC TTA GAA CCA A  4221 AJ_P2 85652 H04 AJ_184 /5AmMC6/CCC AAT GGA ACC 10653 8777 61.9 185   973 CTA GGG TTG AGT TCA A  4222 AJ_P2 85652 H05 AJ_185 /5AmMC6/CCC AAG AAC ACT 10653 8730 61 186   974 TGA GCA GAC GTT TCA A  4223 AJ_P2 85652 H06 AJ_186 /5AmMC6/CCC AAT CGA AGG 10653 8763 58.8 187   975 AAA GCA TGA CTC TAA A  4224 AJ_P2 85652 H07 AJ_187 /5AmMC6/CCC AAC TTA GTG 10653 8761 59.3 188   976 AGA GTG CTA CTC AGA A  4225 AJ_P2 85652 H08 AJ_188 /5AmMC6/CCC AAA CTT GTT 10653 8736 59.7 189   977 GAA GTG CTT CAC AGA A  4226 AJ_P2 85652 H09 AJ_189 /5AmMC6/CCC AAG TGC TAA 10653 8672 60.5 190   978 CAC TGT TCT CCA TGA A  4227 AJ_P2 85652 H10 AJ_190 /5AmMC6/CCC AAC CCT TAG 10653 8666 61.7 191   979 ACC TGA ACA TCG TGA A  4228 AJ_P2 85652 H11 AJ_191 /5AmMC6/CCC AAC TTA AAG 10653 8770 59.2 192   980 GGT AGA CCT AGT CGA A  4229 AJ_P2 85652 H12 AJ_192 /5AmMC6/CCC AAG GCA TAG 10653 8712 60.1 193   981 ACC TGT CGT TCT TAA A  4230 AJ_P3 85652 A01 AJ_193 /5AmMC6/CCC AAA GCG TTT 10653 8761 60.1 194   983 CTA GGG TAG TAA CCA A  4231 AJ_P3 85652 A02 AJ_194 /5AmMC6/CCC AAG CAA ACT 10653 8705 59.7 195   984 TTC CAA GAC GTT GTA A  4232 AJ_P3 85652 A03 AJ_195 /5AmMC6/CCC AAT CTG GTA 10653 8672 60.8 196   985 ACT GCT TTC GAA CCA A  4233 AJ_P3 85652 A04 AJ_196 /5AmMC6/CCC AAT CAG GAG 10653 8779 59.4 197   986 AGC AAG TAC TAG TCA A  4234 AJ_P3 85652 A05 AJ_197 /5AmMC6/CCC AAA CAT TGT 10653 8687 59.9 198   987 GTC GTT AAC GCT TCA A  4235 AJ_P3 85652 A06 AJ_198 /5AmMC6/CCC AAG AGG TAC 10653 8770 59.5 199   988 TTA GGC ATA ACC GTA A  4236 AJ_P3 85652 A07 AJ_199 /5AmMC6/CCC AAA AAC GGT 10653 8739 62.2 200   989 TTG GCA AAC TGA CCA A  4237 AJ_P3 85652 A08 AJ_200 /5AmMC6/CCC AAC ATA AGG 10653 8755 62.1 201   990 CAA GGG TAC TGT CCA A  4238 AJ_P3 85652 A09 AJ_201 /5AmMC6/CCC AAA TGA CGA 10653 8795 61.6 202   991 CAG GAG TAG TGT CCA A  4239 AJ_P3 85652 A10 AJ_202 /5AmMC6/CCC AAG ACC TTT 10653 8712 60.4 203   992 GCG TTT ACA GGA CTA A  4240 AJ_P3 85652 A11 AJ_203 /5AmMC6/CCC AAG TCT AGA 10653 8699 59.6 204   993 GTC AAC ACA GCA CTA A  4241 AJ_P3 85652 A12 AJ_204 /5AmMC6/CCC AAG AGA GCT 10653 8715 61.5 205   994 TAA CCA GAC TGT CCA A  4242 AJ_P3 85652 B01 AJ_205 /5AmMC6/CCC AAG ACC ATA 10653 8690 60.1 206   995 CTG CAC ATT AGG CTA A  4243 AJ_P3 85652 B02 AJ_206 /5AmMC6/CCC AAG CCA ACT 10653 8706 61.8 207   996 ACG TCA TAG TGG TCA A  4244 AJ_P3 85652 B03 AJ_207 /5AmMC6/CCC AAT GTC GAA 10653 8699 60.2 208   997 CGT ACC AAG ACC ATA A  4245 AJ_P3 85652 B04 AJ_208 /5AmMC6/CCC AAC GTG TAG 10653 8761 60 209   998 GAA GTT CGT ACT CAA A  4246 AJ_P3 85652 B05 AJ_209 /5AmMC6/CCC AAA AAC CGT 10653 8730 61.3 210   999 AAG CCT TCA TGG TGA A  4247 AJ_P3 85653 B06 AJ_210 /5AmMC6/CCC AAT CGG AAA 10653 8745 59.7 211   000 CGC AAG TTC ATG TTA A  4248 AJ_P3 85653 B07 AJ_211 /5AmMC6/CCC AAT CGG TAA 10653 8763 58.3 212   001 CTA GAA AGC ACA GTA A  4249 AJ_P3 85653 B08 AJ_212 /5AmMC6/CCC AAG TCG AAG 10653 8779 60.1 213   002 TAG GCT AAA GTC CAA A  4250 AJ_P3 85653 B09 AJ_213 /5AmMC6/CCC AAA CGG TAG 10653 8712 59.8 214   003 TAC CTT GTC GTC ATA A  4251 AJ_P3 85653 B10 AJ_214 /5AmMC6/CCC AAC ATT TGG 10653 8727 59.6 215   004 AAG TTG CAT CCT GTA A  4252 AJ_P3 85653 B11 AJ_215 /5AmMC6/CCC AAC GAA GTG 10653 8746 62.6 216   005 TTG GTC AAG TCC ACA A  4253 AJ_P3 85653 B12 AJ_216 /5AmMC6/CCC AAT CAA GGA 10653 8779 60.5 217   006 AAG GAC TAG TTC GCA A  4254 AJ_P3 85653 C01 AJ_217 /5AmMC6/CCC AAC GAA ACT 10653 8723 58.3 218   007 TAC AAC GTA GGA CTA A  4255 AJ_P3 85653 C02 AJ_218 /5AmMC6/CCC AAG GCA TGC 10653 8727 59 219   008 TTA GTC TGA ACT TTA A  4256 AJ_P3 85653 C03 AJ_219 /5AmMC6/CCC AAG AAC CGT 10653 8672 60.5 220   009 TCC CAT GTA GCT TTA A  4257 AJ_P3 85653 C04 AJ_220 /5AmMC6/CCC AAG GCA TAA 10653 8745 59.1 221   010 AGT GTT CTC TCG AAA A  4258 AJ_P3 85653 C05 AJ_221 /5AmMC6/CCC AAG GCT ACC 10653 8739 59.6 222   011 CTT AAA GAG GAC ATA A  4259 AJ_P3 85653 C06 AJ_222 /5AmMC6/CCC AAG TCC TAG 10653 8712 59.8 223   012 ACT TCG GTT CGT AAA A  4260 AJ_P3 85653 C07 AJ_223 /5AmMC6/CCC AAG GAA CCT 10653 8699 60.2 224   013 TGT ACA ACA CGA CTA A  4261 AJ_P3 85653 C08 AJ_224 /5AmMC6/CCC AAC ACG TTG 10653 8779 59.3 225   014 TAG AGA CAG AGA CTA A  4262 AJ_P3 85653 C09 AJ_225 /5AmMC6/CCC AAT CCA AGC 10653 8730 61 226   015 ACA AGG TAG GTT TCA A  4263 AJ_P3 85653 C10 AJ_226 /5AmMC6/CCC AAA GCC ATA 10653 8736 59 227   016 CTA GTT GTT GTC GAA A  4264 AJ_P3 85653 C11 AJ_227 /5AmMC6/CCC AAC GAG TAC 10653 8779 59.2 228   017 CAT AGT GAA GGA CTA A  4265 AJ_P3 85653 C12 AJ_228 /5AmMC6/CCC AAC ATT TGC 10653 8770 60.3 229   018 CAA GGG TAG AGA CTA A  4266 AJ_P3 85653 D01 AJ_229 /5AmMC6/CCC AAC GAC TGT 10653 8687 59.3 230   019 TTC CGT AAA GCT TTA A  4267 AJ_P3 85653 D02 AJ_230 /5AmMC6/CCC AAG GAG TAC 10653 8779 59.7 231   020 GAG ACA TCA AGC TTA A  4268 AJ_P3 85653 D03 AJ_231 /5AmMC6/CCC AAT GGA CTG 10653 8777 61.6 232   021 TCT GGA GTA ACG TCA A  4269 AJ_P3 85653 D04 AJ_232 /5AmMC6/CCC AAA CCG TTA 10653 8752 60.5 233   022 CAG GTT TAG TGT CGA A  4270 AJ_P3 85653 D05 AJ_233 /5AmMC6/CCC AAT GAC AAA 10653 8763 58.6 234   023 GAG TAC GAA CTG CTA A  4271 AJ_P3 85653 D06 AJ_234 /5AmMC6/CCC AAT CAC AAG 10653 8723 59 235   024 TGA CAA AGT ACG CTA A  4272 AJ_P3 85653 D07 AJ_235 /5AmMC6/CCC AAC TGT AAA 10653 8736 58.1 236   025 GAG TTG CTA GCT CTA A  4273 AJ_P3 85653 D08 AJ_236 /5AmMC6/CCC AAT GGG AAC 10653 8795 62.3 237   026 ACT GTG AAG TCG ACA A  4274 AJ_P3 85653 D09 AJ_237 /5AmMC6/CCC AAA TTG CGT 10653 8752 61.9 238   027 TTG GTC AAC TGG ACA A  4275 AJ_P3 85653 D10 AJ_238 /5AmMC6/CCC AAC GAA GGT 10653 8746 62 239   028 TCA GGT TAG TCC ACA A  4276 AJ_P3 85653 D11 AJ_239 /5AmMC6/CCC AAA TGC TGT 10653 8687 59.7 240   029 GTT AAC CTT TAG CCA A  4277 AJ_P3 85653 D12 AJ_240 /5AmMC6/CCC AAC CAC TTG 10653 8712 59.5 241   030 TAG TAC TAG GTT CGA A  4278 AJ_P3 85653 E01 AJ_241 /5AmMC6/CCC AAC CCA TAG 10653 8712 60.3 242   031 AGG TTT CAC GTT GTA A  4279 AJ_P3 85653 E02 AJ_242 /5AmMC6/CCC AAC TAG GAA 10653 8763 58.7 243   032 AGA GTT CAA CGC ATA A  4280 AJ_P3 85653 E03 AJ_243 /5AmMC6/CCC AAT CCG AAG 10653 8779 59.6 244   033 AAA GGT CTA CAG GTA A  4281 AJ_P3 85653 E04 AJ_244 /5AmMC6/CCC AAT GGA AAC 10653 8714 58.9 245   034 CCT TAA GAA CTG CTA A  4282 AJ_P3 85653 E05 AJ_245 /5AmMC6/CCC AAG CAA CAT 10653 8699 60.5 246   035 AAC CTT GAC TCA GGA A  4283 AJ_P3 85653 E06 AJ_246 /5AmMC6/CCC AAT AGA ACC 10653 8723 58.4 247   036 ACA GAC TTT AGC AGA A  4284 AJ_P3 85653 E07 AJ_247 /5AmMC6/CCC AAT CAC AAG 10653 8763 59.1 248   037 AGG TTC GTA CGA AAA A  4285 AJ_P3 85653 E08 AJ_248 /5AmMC6/CCC AAA GCT TTG 10653 8705 59.3 249   038 TCT CCA GTA CGA AAA A  4286 AJ_P3 85653 E09 AJ_249 /5AmMC6/CCC AAT CGG AAG 10653 8770 60.7 250   039 GTG TTC AGT AAA CCA A  4287 AJ_P3 85653 E10 AJ_250 /5AmMC6/CCC AAA GTG CAT 10653 8723 59.4 251   040 TCC AAG AAA CGA CTA A  4288 AJ_P3 85653 E11 AJ_251 /5AmMC6/CCC AAG ACG TAA 10653 8690 60.1 252   041 CCA TCG AAC TCG TTA A  4289 AJ_P3 85653 E12 AJ_252 /5AmMC6/CCC AAC CGT AGA 10653 8687 59.3 253   042 ACG TTC TTT GCT TAA A  4290 AJ_P3 85653 F01 AJ_253 /5AmMC6/CCC AAG AGC TCA 10653 8755 61.6 254   043 AGG GTT CTA GAA CCA A  4291 AJ_P3 85653 F02 AJ_254 /5AmMC6/CCC AAT CGG TAG 10653 8770 60 255   044 TTA CGA GTA AAG CCA A  4292 AJ_P3 85653 F03 AJ_255 /5AmMC6/CCC AAG ACA ACT 10653 8666 61.5 256   045 AGC TCT TGG ACT CCA A  4293 AJ_P3 85653 F04 AJ_256 /5AmMC6/CCC AAT GAC GAA 10653 8739 59.5 257   046 GGA CAC TTA GAC CTA A  4294 AJ_P3 85653 F05 AJ_257 /5AmMC6/CCC AAC CGT AGA 10653 8714 59.1 258   047 ACA TTT GAA GCC ATA A  4295 AJ_P3 85653 F06 AJ_258 /5AmMC6/CCC AAC CAC TCG 10653 8675 62.2 259   048 AAC ATG GTA ACG TCA A  4296 AJ_P3 85653 F07 AJ_259 /5AmMC6/CCC AAT CGA ACC 10653 8690 60.7 260   049 GTA ACC ATT TCA GGA A  4297 AJ_P3 85653 F08 AJ_260 /5AmMC6/CCC AAC TAG TGG 10653 8761 60.5 261   050 TTG GAA CAT GCA CTA A  4298 AJ_P3 85653 F09 AJ_261 /5AmMC6/CCC AAG TGC TTA 10653 8721 60.8 262   051 CTG TCC ATC GGA AAA A  4299 AJ_P3 85653 F10 AJ_262 /5AmMC6/CCC AAT GAG TCT 10653 8687 58.8 263   052 GCA TCT CTT TCA AGA A  4300 AJ_P3 85653 F11 AJ_263 /5AmMC6/CCC AAT AGG ACA 10653 8739 59.8 264   053 AAG ACG TCT TAC CGA A  4301 AJ_P3 85653 F12 AJ_264 /5AmMC6/CCC AAT CAT AGG 10653 8779 59.3 265   054 CTA AGG GAA GAC CTA A  4302 AJ_P3 85653 G01 AJ_265 /5AmMC6/CCC AAC AGA GGT 10653 8795 61.7 266   055 AAA GTC CAG TGG TCA A  4303 AJ_P3 85653 G02 AJ_266 /5AmMC6/CCC AAG ACC ACT 10653 8690 60.7 267   056 ACA ACG TTG CAT GTA A  4304 AJ_P3 85653 G03 AJ_267 /5AmMC6/CCC AAT AGA CCA 10653 8739 60.2 268   057 CAA GCA TCG TTA GGA A  4305 AJ_P3 85653 G04 AJ_268 /5AmMC6/CCC AAG TCA CTC 10653 8681 59.8 269   058 ACC TAA GTT CGG TAA A  4306 AJ_P3 85653 G05 AJ_269 /5AmMC6/CCC AAG CTT TCA 10653 8690 60.3 270   059 AGT ACC ACA CGA GTA A  4307 AJ_P3 85653 G06 AJ_270 /5AmMC6/CCC AAG TCA CAT 10653 8697 61.4 271   060 CCT CTA GGG TTC GAA A  4308 AJ_P3 85653 G07 AJ_271 /5AmMC6/CCC AAA AAC GTT 10653 8736 59.8 272   061 CAT TTG GTC TGA CGA A  4309 AJ_P3 85653 G08 AJ_272 /5AmMC6/CCC AAC TGT CCA 10653 8730 61.2 273   062 TTC GGA ACG TGA AAA A  4310 AJ_P3 85653 G09 AJ_273 /5AmMC6/CCC AAA GTT CTT 10653 8727 59.1 274   063 TCT TCA GCA AGG GTA A  4311 AJ_P3 85653 G10 AJ_274 /5AmMC6/CCC AAT AGT CCT 10653 8712 59.5 275   064 GTC GTT AGA ACC GTA A  4312 AJ_P3 85653 G11 AJ_275 /5AmMC6/CCC AAC GTA CAT 10653 8690 60.2 276   065 CCC TTA GAA ACG TGA A  4313 AJ_P3 85653 G12 AJ_276 /5AmMC6/CCC AAC GGT TCA 10653 8687 59.7 277   066 GCA CTT TAC ATT TGA A  4314 AJ_P3 85653 H01 AJ_277 /5AmMC6/CCC AAT GCG TAA 10653 8672 60.7 278   067 ACT CGT TGT CCT ACA A  4315 AJ_P3 85653 H02 AJ_278 /5AmMC6/CCC AAT CGG TAA 10653 8687 59.4 279   068 ACC TGT TTC GCT TAA A  4316 AJ_P3 85653 H03 AJ_279 /5AmMC6/CCC AAG TGC AAG 10653 8770 61.4 280   069 CAC AGG TGA CAT TTA A  4317 AJ_P3 85653 H04 AJ_280 /5AmMC6/CCC AAG GGT ACA 10653 8795 60.9 281   070 GAC GAG TAA CTC TGA A  4318 AJ_P3 85653 H05 AJ_281 /5AmMC6/CCC AAA CCC TAG 10653 8672 59.1 282   071 TAG TTC TAC TCG TGA A  4319 AJ_P3 85653 H06 AJ_282 /5AmMC6/CCC AAG TAA CCC 10653 8706 61 283   072 TTC CGT AGG ACA GTA A  4320 AJ_P3 85653 H07 AJ_283 /5AmMC6/CCC AAT TTA GTC 10653 8672 60.3 284   073 ACT CTG GTC AAC CGA A  4321 AJ_P3 85653 H08 AJ_284 /5AmMC6/CCC AAG TAC ACA 10653 8715 61.6 285   074 ACC TCT GGT AAC GGA A  4322 AJ_P3 85653 H09 AJ_285 /5AmMC6/CCC AAC ACA AGT 10653 8795 62.2 286   075 TCA GGT AGG AGT GCA A  4323 AJ_P3 85653 H10 AJ_286 /5AmMC6/CCC AAC TAA AGG 10653 8696 59.4 287   076 TGT TTA CGC TTC CAA A  4324 AJ_P3 85653 H11 AJ_287 /5AmMC6/CCC AAC TGA AGT 10653 8777 61.4 288   077 TGG TCT ACC TGA GGA A  4325 AJ_P3 85653 H12 AJ_288 /5AmMC6/CCC AAT GTC GTA 10653 8672 60.8 289   078 AGT TCC TCA ACT GCA A  4326 AJ_P4 85653 A01 AJ_289 /5AmMC6/CCC AAA CCT GAG 10653 8712 60.5 290   080 ACC TGT GTT TCG TAA A  4327 AJ_P4 85653 A02 AJ_290 /5AmMC6/CCC AAT AGG CTA 10653 8723 58.4 291   081 GCT CAA CCA TAA AGA A  4328 AJ_P4 85653 A03 AJ_291 /5AmMC6/CCC AAG TTG ACA 10653 8675 61.8 292   082 ACG CTA CCC TAG ACA A  4329 AJ_P4 85653 A04 AJ_292 /5AmMC6/CCC AAT CAC GAA 10653 8754 59.7 293   083 GTG AGC TTG TCA AAA A  4330 AJ_P4 85653 A05 AJ_293 /5AmMC6/CCC AAT GAA ACC 10653 8690 61.2 294   084 GTA ACT CAC TTG GCA A  4331 AJ_P4 85653 A06 AJ_294 /5AmMC6/CCC AAC TTA GCA 10653 8763 59.2 295   085 CAA AGT GTA GAA GCA A  4332 AJ_P4 85653 A07 AJ_295 /5AmMC6/CCC AAT GCG TAG 10653 8763 59.1 296   086 AAC CAT GTA CAA AGA A  4333 AJ_P4 85653 A08 AJ_296 /5AmMC6/CCC AAG AGT TGC 10653 8761 60.4 297   087 TTC GGT ACT CAA AGA A  4334 AJ_P4 85653 A09 AJ_297 /5AmMC6/CCC AAG CGT AGT 10653 8779 60.3 298   088 TCG GAA ACA CTA AGA A  4335 AJ_P4 85653 A10 AJ_298 /5AmMC6/CCC AAA AGA GTC 10653 8690 59.4 299   089 TTA CCG TAC TAC CGA A  4336 AJ_P4 85653 A11 AJ_299 /5AmMC6/CCC AAA AAC GGT 10653 8706 61.7 300   090 AGG TCT CTG ACT CCA A  4337 AJ_P4 85653 A12 AJ_300 /5AmMC6/CCC AAG GTC AGT 10653 8706 62.4 301   091 TAA GCC AAC CCT TGA A  4338 AJ_P4 85653 B01 AJ_301 /5AmMC6/CCC AAA CCA GTC 10653 8672 60.1 302   092 TCT CAG TTT ACG TGA A  4339 AJ_P4 85653 B02 AJ_302 /5AmMC6/CCC AAT AAG ACA 10653 8699 60.7 303   093 AGG ACT TCC ATG CCA A  4340 AJ_P4 85653 B03 AJ_303 /5AmMC6/CCC AAG TCG AGA 10653 8770 59.9 304   094 ACA TGG AAG TCC TTA A  4341 AJ_P4 85653 B04 AJ_304 /5AmMC6/CCC AAT GCA GAG 10653 8763 58.4 305   095 AAA GTA CAT ACC GTA A  4342 AJ_P4 85653 B05 AJ_305 /5AmMC6/CCC AAG TGC ACT 10653 8779 60.5 306   096 TAA GGA CAA CAG GTA A  4343 AJ_P4 85653 B06 AJ_306 /5AmMC6/CCC AAA CCT GTC 10653 8721 60.2 307   097 TTA AGG CAT ACG GTA A  4344 AJ_P4 85653 B07 AJ_307 /5AmMC6/CCC AAG TCT CTA 10653 8752 59.6 308   098 AGT AGG CAT GCT GTA A  4345 AJ_P4 85653 B08 AJ_308 /5AmMC6/CCC AAC GTC TGA 10653 8770 59.8 309   099 CAT TGG AGA GAA CTA A  4346 AJ_P4 85653 B09 AJ_309 /5AmMC6/CCC AAA AAG CTC 10653 8696 59.3 310   100 ACG TCT TGG TCT TAA A  4347 AJ_P4 85653 B10 AJ_310 /5AmMC6/CCC AAG GGT AAC 10653 8770 60 311   101 AGA CAC TTT AGC GTA A  4348 AJ_P4 85653 B11 AJ_311 /5AmMC6/CCC AAT GAC CTA 10653 8795 60.9 312   102 CGA GTG GAG AGT ACA A  4349 AJ_P4 85653 B12 AJ_312 /5AmMC6/CCC AAA GCT TGC 10653 8723 59.2 313   103 GAA ACC TAA CTA AGA A  4350 AJ_P4 85653 C01 AJ_313 /5AmMC6/CCC AAT GTC GAC 10653 8699 59.6 314   104 AGA CCA TAC CTA AGA A  4351 AJ_P4 85653 C02 AJ_314 /5AmMC6/CCC AAG GTC AAC 10653 8675 62.6 315   105 AAG CCA TAC GTT CCA A  4352 AJ_P4 85653 C03 AJ_315 /5AmMC6/CCC AAC TGG TTA 10653 8770 59.5 316   106 CTA CGA ACA GGA GTA A  4353 AJ_P4 85653 C04 AJ_316 /5AmMC6/CCC AAT AGA GAC 10653 8690 59.1 317   107 GTT ACT CCT AAC CGA A  4354 AJ_P4 85653 C05 AJ_317 /5AmMC6/CCC AAA GAC AGT 10653 8690 60.1 318   108 TGA CAC CTT AGC CTA A  4355 AJ_P4 85653 C06 AJ_318 /5AmMC6/CCC AAA TCG AGA 10653 8690 59.8 319   109 GTT ACA CCT TAC CGA A  4356 AJ_P4 85653 C07 AJ_319 /5AmMC6/CCC AAA CAG GTT 10653 8779 60.4 320   110 TCC AAG AAC TAG GGA A  4357 AJ_P4 85653 C08 AJ_320 /5AmMC6/CCC AAG ACA GGT 10653 8777 61.2 321   111 AGG TCT TGC TAG TCA A  4358 AJ_P4 85653 C09 AJ_321 /5AmMC6/CCC AAG GAG TCT 10653 8715 61.7 322   112 CAA CCG TTA ACC AGA A  4359 AJ_P4 85653 C10 AJ_322 /5AmMC6/CCC AAG AAA CGT 10653 8681 60.7 323   113 ACG CTT CTC CAT TGA A  4360 AJ_P4 85653 C11 AJ_323 /5AmMC6/CCC AAC TTA GGA 10653 8675 61.5 324   114 AGC ACT ACG TAC CCA A  4361 AJ_P4 85653 C12 AJ_324 /5AmMC6/CCC AAG TAA GCT 10658 8657 61.5 325   115 ACG TTC CTG TAC CCA A  6457 AJ_P4 85653 D01 AJ_325 /5AmMC6/CCC AAC CAA GTA 10653 8795 62.1 326   116 AGT GGA CAC TGG TGA A  4363 AJ_P4 85653 D02 AJ_326 /5AmMC6/CCC AAC TGT TTA 10653 8761 60 327   117 CAG AGG TCA GCA GTA A  4364 AJ_P4 85653 D03 AJ_327 /5AmMC6/CCC AAC ACG TCT 10653 8723 58.6 328   118 TAA AGC AGA GAA CTA A  4365 AJ_P4 85653 D04 AJ_328 /5AmMC6/CCC AAG AGG ACT 10653 8697 61.1 329   119 GTC CTA CTT CCA TGA A  4366 AJ_P4 85653 D05 AJ_329 /5AmMC6/CCC AAG AAC ATC 10653 8666 61.6 330   120 TCC ACT GGT CAC GTA A  4367 AJ_P4 85653 D06 AJ_330 /5AmMC6/CCC AAT GAA GCA 10653 8739 60.9 331   121 ACA AGT GGT ACT CCA A  4368 AJ_P4 85653 D07 AJ_331 /5AmMC6/CCC AAT CCG TAA 10653 8779 59.5 332   122 CAG TAG GAG AAC GTA A  4369 AJ_P4 85653 D08 AJ_332 /5AmMC6/CCC AAA CCG TAG 10653 8690 60 333   123 GAA CTA CCA TTC TGA A  4370 AJ_P4 85653 D09 AJ_333 /5AmMC6/CCC AAC CAG TTC 10653 8690 60.8 334   124 GTT CAA ACA GAC TGA A  4371 AJ_P4 85653 D10 AJ_334 /5AmMC6/CCC AAG TTA AAC 10653 8699 60.4 335   125 ATC CAG AGC TCA CGA A  4372 AJ_P4 85653 D11 AJ_335 /5AmMC6/CCC AAG TCA CAC 10653 8715 61.9 336   126 AAC CTA GAG CTT GGA A  4373 AJ_P4 85653 D12 AJ_336 /5AmMC6/CCC AAC ATG TTA 10653 8752 61 337   127 GGG TTA CCT TGG CAA A  4374 AJ_P4 85653 E01 AJ_337 /5AmMC6/CCC AAG TCA AAG 10653 8666 61.7 338   128 GTA CTC CAC TTC CGA A  4375 AJ_P4 85653 E02 AJ_338 /5AmMC6/CCC AAG TAG AAC 10653 8699 60 339   129 GTC AAC CAC TTA CGA A  4376 AJ_P4 85653 E03 AJ_339 /5AmMC6/CCC AAG GAG ACT 10653 8697 60.5 340   130 TGT CCT ACT CTA CGA A  4377 AJ_P4 85653 E04 AJ_340 /5AmMC6/CCC AAT TTC GTA 10653 8687 58.9 341   131 GTA CTC ACT TGC GAA A  4378 AJ_P4 85653 E05 AJ_341 /5AmMC6/CCC AAC CTT GTA 10653 8770 59.5 342   132 CTA GGA AGG AAG CTA A  4379 AJ_P4 85653 E06 AJ_342 /5AmMC6/CCC AAG TCG TAG 10653 8697 62.3 343   133 TTG TCA CAC TGC ACA A  4380 AJ_P4 85653 E07 AJ_343 /5AmMC6/CCC AAC GAA GTT 10653 8672 61 344   134 ACG TCT TTC ATG CCA A  4381 AJ_P4 85653 E08 AJ_344 /5AmMC6/CCC AAA AGG CAT 10653 8730 61.3 345   135 AAG GCT TGT CAT CCA A  4382 AJ_P4 85653 E09 AJ_345 /5AmMC6/CCC AAG TGT CCA 10653 8681 60.8 346   136 TAC GCT TTA CCG AAA A  4383 AJ_P4 85653 E10 AJ_346 /5AmMC6/CCC AAC GGT TGA 10653 8715 62.3 347   137 CAC CAG TTA CCA AGA A  4384 AJ_P4 85653 E11 AJ_347 /5AmMC6/CCC AAG TGT GCA 10653 8697 62.2 348   138 ACC AGT TAC TCC TGA A  4385 AJ_P4 85653 E12 AJ_348 /5AmMC6/CCC AAG CTG ACA 10653 8672 60.1 349   139 GAC TCT CTT TCA TGA A  4386 AJ_P4 85653 F01 AJ_349 /5AmMC6/CCC AAG AAA GCT 10653 8681 59.4 350   140 GTA CCC TTC TCT AGA A  4387 AJ_P4 85653 F02 AJ_350 /5AmMC6/CCC AAA TGT TGC 10653 8714 59 351   141 TAC AAG ACT AAC CGA A  4388 AJ_P4 85653 F03 AJ_351 /5AmMC6/CCC AAG TCT GGA 10653 8777 61.4 352   142 AGT GCT AGT ACG TCA A  4389 AJ_P4 85653 F04 AJ_352 /5AmMC6/CCC AAT CGC AAC 10653 8687 59.4 353   143 TTC GGT ACA TTT GTA A  4390 AJ_P4 85653 F05 AJ_353 /5AmMC6/CCC AAC CTG TAA 10653 8754 59 354   144 CAT TGA AGA AGC GTA A  4391 AJ_P4 85653 F06 AJ_354 /5AmMC6/CCC AAA CTG TTG 10653 8754 59.4 355  145 GAA AGC TGA ACA CTA A  4392 AJ_P4 85653 F07 AJ_355 /5AmMC6/CCC AAG ACG TAG 10653 8779 58.9 356   146 CTT AGA GAG AAC CTA A  4393 AJ_P4 85653 F08 AJ_356 /5AmMC6/CCC AAC ATT GTT 10653 8761 60.7 357   147 GTG GAA CCT CAG AGA A  4394 AJ_P4 85653 F09 AJ_357 /5AmMC6/CCC AAG TGG ACT 10653 8697 61.2 358   148 AGC TTC CTA CAC TGA A  4395 AJ_P4 85653 F10 AJ_358 /5AmMC6/CCC AAA GGA ACT 10653 8723 59.2 359   149 GAC ATT CAA CAC GTA A  4396 AJ_P4 85653 F11 AJ_359 /5AmMC6/CCC AAT GTT CGA 10653 8690 60.2 360   150 GTC CAC AAC TAC AGA A  4397 AJ_P4 85653 F12 AJ_360 /5AmMC6/CCC AAG TAA CTA 10653 8739 59 361   151 CTC ACA GAG CTA GGA A  4398 AJ_P4 85653 G01 AJ_361 /5AmMC6/CCC AAG AGG ACT 10653 8706 61.2 362   152 CAC CAG TAC TTT CGA A  4399 AJ_P4 85653 G02 AJ_362 /5AmMC6/CCC AAT AGC GTT 10653 8687 59 363   153 GTT TCT AAC CAC TGA A  4400 AJ_P4 85653 G03 AJ_363 /5AmMC6/CCC AAC ATT TGT 10653 8736 59 364   154 TAG TAG CAG TCA CGA A  4401 AJ_P4 85653 G04 AJ_364 /5AmMC6/CCC AAT AAC AGC 10653 8699 60.8 365   155 AAG ACC TTG TAG CCA A  4402 AJ_P4 85653 G05 AJ_365 /5AmMC6/CCC AAG ACT CTC 10653 8675 61.9 366   156 CAC ACG TTG AAG ACA A  4403 AJ_P4 85653 G06 AJ_366 /5AmMC6/CCC AAG AAC TCC 10653 8666 61.7 367   157 ATC CTG TTC GAC AGA A  4404 AJ_P4 85653 G07 AJ_367 /5AmMC6/CCC AAG GTT CTA 10653 8681 60.4 368   158 GTT CCA ACT AAC GCA A  4405 AJ_P4 85653 G08 AJ_368 /5AmMC6/CCC AAA GTT GCG 10653 8727 59 369   159 TTT GTC ATA GAC CTA A  4406 AJ_P4 85653 G09 AJ_369 /5AmMC6/CCC AAC GCT TGA 10653 8763 59 370   160 GGT AAA CTA AAC AGA A  4407 AJ_P4 85653 G10 AJ_370 /5AmMC6/CCC AAT AAC GAG 10653 8739 59 371   161 TAG AGC TCT AGA CCA A  4408 AJ_P4 85653 G11 AJ_371 /5AmMC6/CCC AAG TGA GTC 10653 8739 60.5 372   162 ATA GCC ATA AGC CAA A  4409 AJ_P4 85653 G12 AJ_372 /5AmMC6/CCC AAC TTA CGT 10653 8672 60.3 373   163 GAC TTC CAT TCA GGA A  4410 AJ_P4 85653 H01 AJ_373 /5AmMC6/CCC AAA TCA GTG 10653 8672 60.1 374   164 ACT GTC TCT TCA CGA A  4411 AJ_P4 85653 H02 AJ_374 /5AmMC6/CCC AAA GGT ACT 10653 8657 61.4 375   165 GAC TTC CAC TCC TGA A  4412 AJ_P4 85653 H03 AJ_375 /5AmMC6/CCC AAT CGA CAT 10653 8779 59.9 376   166 TAC AGG AAG TAC GGA A  4413 AJ_P4 85653 H04 AJ_376 /5AmMC6/CCC AAC CAC TGG 10653 8739 60.9 377   167 TTA AAC GTA AAC GGA A  4414 AJ_P4 85653 H05 AJ_377 /5AmMC6/CCC AAG TTC ATT 10653 8672 60.7 378   168 CCC TAA GCC TTG GAA A  4415 AJ_P4 85653 H06 AJ_378 /5AmMC6/CCC AAG AAA CTA 10653 8730 60.1 379   169 CTC CAT GGT TAG CGA A  4416 AJ_P4 85653 H07 AJ_379 /5AmMC6/CCC AAC TAA GGG 10653 8745 58.4 380   170 TTA AAG CTT ACC GTA A  4417 AJ_P4 85653 H08 AJ_380 /5AmMC6/CCC AAG AGA CCT 10653 8690 60.1 381   171 GTC ACA CTT TAA CGA A  4418 AJ_P4 85653 H09 AJ_381 /5AmMC6/CCC AAT GAA CAA 10653 8723 59.8 382   172 CAA CAT GCT TAC GGA A  4419 AJ_P4 85653 H10 AJ_382 /5AmMC6/CCC AAT CAG AAA 10653 8763 58.9 383   173 GCA ACA TTC TAG GGA A  4420 AJ_P4 85653 H11 AJ_383 /5AmMC6/CCC AAT AGG CTT 10653 8705 58.8 384   174 GAC TCA TTA AAC CGA A  4421 AJ_P4 85653 H12 AJ_384 /5AmMC6/CCC AAA CTG GTT 10653 8712 60.3 385   175 TGT AGT CCT ACC GAA A  4422 AJ_P5 85653 A01 AJ_385 /5AmMC6/CCC AAA CCT GAC 10653 8687 59 386   177 AGC TTG TTT CTT AGA A  4423 AJ_P5 85653 A02 AJ_386 /5AmMC6/CCC AAC TTG CTA 10653 8770 59.9 387   178 CAT AGA GAG AGT GCA A  4424 AJ_P5 85653 A03 AJ_387 /5AmMC6/CCC AAG GTA AAC 10653 8666 61.5 388   179 CTT CCA GTC TCC AGA A  4425 AJ_P5 85653 A04 AJ_388 /5AmMC6/CCC AAT ACC AAG 10653 8739 60.8 389   180 TAC GCA AAC TGT GGA A  4426 AJ_P5 85653 A05 AJ_389 /5AmMC6/CCC AAC CGT AAA 10653 8730 60.5 390   181 CCT TAA GGT GTA GCA A  4427 AJ_P5 85653 A06 AJ_390 /5AmMC6/CCC AAC ATT GTT 10653 8681 61.6 391   182 TCC CAA GGC ATA GCA A  4428 AJ_P5 85653 A07 AJ_391 /5AmMC6/CCC AAG GTC ATC 10653 8657 61.9 392   183 CTA CTA GCA TTG CCA A  4429 AJ_P5 85653 A08 AJ_392 /5AmMC6/CCC AAG TTC AAC 10653 8681 60.4 393   184 ATC ACT GCT ACG GTA A  4430 AJ_P5 85653 A09 AJ_393 /5AmMC6/CCC AAT TCG CAT 10653 8727 60.1 394   185 GCA TTT AAG GTG TCA A  4431 AJ_P5 85653 A10 AJ_394 /5AmMC6/CCC AAC TTA GCA 10653 8779 59.4 395   186 CTA GAG AAG GAG TCA A  4432 AJ_P5 85653 A11 AJ_395 /5AmMC6/CCC AAG CTC AGG 10653 8777 62.2 396   187 ACA GTT GAG TGT TCA A  4433 AJ_P5 85653 A12 AJ_396 /5AmMC6/CCC AAG TCC TAG 10653 8761 59.7 397   188 CTA AGA GTG TGT CAA A  4434 AJ_P5 85653 B01 AJ_397 /5AmMC6/CCC AAG CTA CAA 10653 8754 59.3 398   189 GCA TAA GTG GTT CAA A  4435 AJ_P5 85653 B02 AJ_398 /5AmMC6/CCC AAG TCA TAC 10653 8739 60 399   190 CAA AGC TGA GAC GTA A  4436 AJ_P5 85653 B03 AJ_399 /5AmMC6/CCC AAT TTA GCA 10653 8754 58 400   191 TAG ACG AGA GAC TCA A  4437 AJ_P5 85653 B04 AJ_400 /5AmMC6/CCC AAT TTC ATG 10653 8745 59.4 401   192 TAA CGA CAG TGA GCA A  4438 AJ_P5 85653 B05 AJ_401 /5AmMC6/CCC AAT GCA CTT 10653 8754 58.6 402   193 CGT AGA GTA AGA ACA A  4439 AJ_P5 85653 B06 AJ_402 /5AmMC6/CCC AAA CGT TGT 10653 8752 60.5 403   194 CTC TGT AGT GGA ACA A  4440 AJ_P5 85653 B07 AJ_403 /5AmMC6/CCC AAC CGA AGT 10653 8699 60.8 404   195 TAG CAA ACC TCA TGA A  4441 AJ_P5 85653 B08 AJ_404 /5AmMC6/CCC AAC ATT TAG 10653 8754 58.8 405   196 AAG GAC TTC GAA CGA A  4442 AJ_P5 85653 B09 AJ_405 /5AmMC6/CCC AAG TTC CAA 10653 8675 62 406   197 CAC TCA GAC AGG TCA A  4443 AJ_P5 85653 B10 AJ_406 /5AmMC6/CCC AAT GAC AAC 10653 8706 61.7 407   198 CTC TCA GAG TGG TCA A  4444 AJ_P5 85653 B11 AJ_407 /5AmMC6/CCC AAG CCT AGG 10653 8777 61 408   199 TAG GTT CTG GAA CTA A  4445 AJ_P5 85653 B12 AJ_408 /5AmMC6/CCC AAT CGA ACA 10653 8690 60.6 409   200 CAC CAT GTT ACT GGA A  4446 AJ_P5 85653 C01 AJ_409 /5AmMC6/CCC AAT AGT CTA 10653 8727 59.3 410   201 ACT GTT GGC TTG CAA A  4447 AJ_P5 85653 C02 AJ_410 /5AmMC6/CCC AAA AGC TAG 10653 8681 59.8 411   202 GTA CCT TCT TAC CGA A  4448 AJ_P5 85653 C03 AJ_411 /5AmMC6/CCC AAC TCA GAG 10653 8770 60 412   203 TAC AGA GAG TTT GCA A  4449 AJ_P5 85653 C04 AJ_412 /5AmMC6/CCC AAG ACA CGT 10653 8795 61.4 413   204 CAT AGG AGT GTA GCA A  4450 AJ_P5 85653 C05 AJ_413 /5AmMC6/CCC AAT TAA GCA 10653 8763 59.2 414   205 TAA CGA GAC AGT GCA A  4451 AJ_P5 85653 C06 AJ_414 /5AmMC6/CCC AAG TGT CCA 10653 8795 62.6 415   206 CAT GAG GTG AAA GCA A  4452 AJ_P5 85653 C07 AJ_415 /5AmMC6/CCC AAC TAA AGG 10653 8770 60.6 416   207 GTT GAA CGT TCC AGA A  4453 AJ_P5 85653 C08 AJ_416 /5AmMC6/CCC AAA TCG CTT 10653 8727 59.1 417   208 TCT TTA GTG GAG ACA A  4454 AJ_P5 85653 C09 AJ_417 /5AmMC6/CCC AAA GGT CTT 10653 8696 60.1 418   209 CAC TTT GTG CAC AAA A  4455 AJ_P5 85653 C10 AJ_418 /5AmMC6/CCC AAG GCT TAA 10653 8755 62.3 419   210 GGT GAA CCA TCG ACA A  4456 AJ_P5 85653 C11 AJ_419 /5AmMC6/CCC AAC TGT AGA 10653 8699 59.3 420   211 GCT ACC AAC ACT AGA A  4457 AJ_P5 85653 C12 AJ_420 /5AmMC6/CCC AAC TAA GGG 10653 8752 60.5 421   212 TTG TTA CGT TAG CCA A  4458 AJ_P5 85653 D01 AJ_421 /5AmMC6/CCC AAG TGG TAC 10653 8697 61.4 422   213 TCA GCT ACA TCG TCA A  4459 AJ_P5 85653 D02 AJ_422 /5AmMC6/CCC AAG TCC AAA 10653 8675 62.3 423   214 CAC CTT GAG AGC TCA A  4460 AJ_P5 85653 D03 AJ_423 /5AmMC6/CCC AAT CAC AAG 10653 8779 60.1 424   215 CTT AGA GTG GAG ACA A  4461 AJ_P5 85653 D04 AJ_424 /5AmMC6/CCC AAC TTT GAC 10653 8752 60.9 425   216 TTT GGC AAC TAG GGA A  4462 AJ_P5 85653 D05 AJ_425 /5AmMC6/CCC AAC CTC AGT 10653 8737 61 426   217 CTA AGG GTA GTG TCA A  4463 AJ_P5 85653 D06 AJ_426 /5AmMC6/CCC AAA CAC CTG 10653 8715 61.6 427   218 TCC AGA GAG TGT ACA A  4464 AJ_P5 85653 D07 AJ_427 /5AmMC6/CCC AAC ATA GTT 10653 8745 59.2 428   219 GTG AAG CAT CGC TAA A  4465 AJ_P5 85653 D08 AJ_428 /5AmMC6/CCC AAA CGT GTT 10653 8752 60.6 429   220 GTT GTA CCC TAG GAA A  4466 AJ_P5 85653 D09 AJ_429 /5AmMC6/CCC AAA CTT TGG 10653 8754 59.4 430   221 TAG AAA CGT AGC CAA A  4467 AJ_P5 85653 D10 AJ_430 /5AmMC6/CCC AAC TCA GTT 10653 8736 59.9 431   222 GCA TTA AAG TGT GCA A  4468 AJ_P5 85653 D11 AJ_431 /5AmMC6/CCC AAA CTA CTG 10653 8712 60.2 432   223 TTC TGG ACT TCG GAA A  4469 AJ_P5 85653 D12 AJ_432 /5AmMC6/CCC AAA GAG CAT 10653 8779 60 433   224 TAG GAC TGT ACG ACA A  4470 AJ_P5 85653 E01 AJ_433 /5AmMC6/CCC AAC ACC ATG 10653 8746 62.3 434   225 CTG AGT GGT AAG TCA A  4471 AJ_P5 85653 E02 AJ_434 /5AmMC6/CCC AAC TGG AAC 10653 8795 62.2 435   226 ACG TGT GGT AGA ACA A  4472 AJ_P5 85653 E03 AJ_435 /5AmMC6/CCC AAC CTC AGA 10653 8657 62 436   227 ACT CGT TGG TTA CCA A  4473 AJ_P5 85653 E04 AJ_436 /5AmMC6/CCC AAT GCC ATA 10653 8687 59.3 437   228 ACG CTT GTA CTT GTA A  4474 AJ_P5 85653 E05 AJ_437 /5AmMC6/CCC AAA ACC TTG 10653 8763 59 438   229 TAG ACA AGA AGC GTA A  4475 AJ_P5 85653 E06 AJ_438 /5AmMC6/CCC AAC ACA TGT 10653 8779 59.8 439   230 TAG AGA CGA CAG GTA A  4476 AJ_P5 85653 E07 AJ_439 /5AmMC6/CCC AAG GTA CTC 10653 8672 59.4 440   231 TAA CTT GCA GTC CTA A  4477 AJ_P5 85653 E08 AJ_440 /5AmMC6/CCC AAT GCC AAC 10653 8699 60.9 441   232 CTC AAG AAG TGT ACA A  4478 AJ_P5 85653 E09 AJ_441 /5AmMC6/CCC AAC TAA AGT 10653 8739 61.2 442   233 TGG GAA CGC ATC ACA A  4479 AJ_P5 85653 E10 AJ_442 /5AmMC6/CCC AAG GAC TAC 10653 8666 61 443   234 TCC ACT GTC ATC AGA A  4480 AJ_P5 85653 E11 AJ_443 /5AmMC6/CCC AAG AAC CGT 10653 8657 61 444   235 AGT TCC TTC CCT AGA A  4481 AJ_P5 85653 E12 AJ_444 /5AmMC6/CCC AAC TTT GAG 10653 8752 60.1 445   236 GTG AGA CTC GTT ACA A  4482 AJ_P5 85653 F01 AJ_445 /5AmMC6/CCC AAT CAG AGA 10653 8739 60.1 446   237 AGA GTT CGT CAC ACA A  4483 AJ_P5 85653 F02 AJ_446 /5AmMC6/CCC AAG TTT CAT 10653 8672 60.5 447   238 TCC TCA GAG CTG ACA A  4484 AJ_P5 85653 F03 AJ_447 /5AmMC6/CCC AAG TTG TCA 10653 8657 61.8 448   239 CTC CTG AGC ACT ACA A  4485 AJ_P5 85653 F04 AJ_448 /5AmMC6/CCC AAA AGG TTC 10653 8681 61.5 449   240 ATC GCT TTG ACC ACA A  4486 AJ_P5 85653 F05 AJ_449 /5AmMC6/CCC AAT GCC AAG 10653 8752 61.2 450   241 ACT TGT GGT GTT ACA A  4487 AJ_P5 85653 F06 AJ_450 /5AmMC6/CCC AAA GGC TTC 10653 8739 60.4 451   242 GGT AAC ACT AAC AGA A  4488 AJ_P5 85653 F07 AJ_451 /5AmMC6/CCC AAC AGC TAG 10653 8752 61.1 452   243 CAT GGT TTG GTT ACA A  4489 AJ_P5 85653 F08 AJ_452 /5AmMC6/CCC AAG CCA TTA 10653 8657 62.2 453   244 GCC TAG TTG TCC ACA A  4490 AJ_P5 85653 F09 AJ_453 /5AmMC6/CCC AAC GGT ACA 10653 8777 62.7 454   245 ACG GTT GGG TTT ACA A  4491 AJ_P5 85653 F10 AJ_454 /5AmMC6/CCC AAC ACC AGT 10653 8715 62.5 455   246 TGG ACA GGA CAT TCA A  4492 AJ_P5 85653 F11 AJ_455 /5AmMC6/CCC AAT CTC AGA 10653 8786 61.8 456   247 CTG GAA GGG TTG ACA A  4493 AJ_P5 85653 F12 AJ_456 /5AmMC6/CCC AAG TGT GAC 10653 8739 60.9 457   248 GAA CCT CAA ACA TGA A  4494 AJ_P5 85653 G01 AJ_457 /5AmMC6/CCC AAT GCG TAC 10653 8779 60.1 458   249 AGG TAC ATA GGA CAA A  4495 AJ_P5 85653 G02 AJ_458 /5AmMC6/CCC AAC AGT TAA 10653 8763 59.1 459   250 AGG ACA TGA GCT CAA A  4496 AJ_P5 85653 G03 AJ_459 /5AmMC6/CCC AAT CCG AAA 10653 8770 60.3 460   251 GGG TTA CAG TTA CGA A  4497 AJ_P5 85653 G04 AJ_460 /5AmMC6/CCC AAC ATT GTG 10653 8721 61.6 461   252 AAA GTG CAG TTC CCA A  4498 AJ_P5 85653 G05 AJ_461 /5AmMC6/CCC AAA ACC ATG 10653 8675 62.5 462   253 AGG TCA CGT TAC CCA A  4499 AJ_P5 85653 G06 AJ_462 /5AmMC6/CCC AAT CAA GGA 10653 8739 60.3 463   254 GAA ACG TGT ACC TCA A  4500 AJ_P5 85653 G07 AJ_463 /5AmMC6/CCC AAT CAG GAG 10653 8795 60.6 464   255 ACG ACT AGT AGG TCA A  4501 AJ_P5 85653 G08 AJ_464 /5AmMC6/CCC AAG GAC TAG 10653 8706 61 465   256 GTC ACA CAT CTC TGA A  4502 AJ_P5 85653 G09 AJ_465 /5AmMC6/CCC AAC ATA GAG 10653 8739 59.5 466   257 AGG ACA TCT TCG ACA A  4503 AJ_P5 85653 G10 AJ_466 /5AmMC6/CCC AAC GAA CTC 10653 8666 62.3 467   258 ATC CTT GTG GAC ACA A  4504 AJ_P5 85653 G11 AJ_467 /5AmMC6/CCC AAC AGT TGG 10653 8761 61.5 468   259 TGA GTT CAT GCA CAA A  4505 AJ_P5 85653 G12 AJ_468 /5AmMC6/CCC AAC ATA GGA 10653 8795 62.3 469   260 CAG GAG TGT TGC ACA A  4506 AJ_P5 85653 H01 AJ_469 /5AmMC6/CCC AAC TAG TAG 10653 8779 59.8 470   261 AAG ACT GCA TGG ACA A  4507 AJ_P5 85653 H02 AJ_470 /5AmMC6/CCC AAT AGA GCA 10653 8779 60.2 471   262 AGA ACC TCA GTT GGA A  4508 AJ_P5 85653 H03 AJ_471 /5AmMC6/CCC AAC CAT GTG 10653 8777 62.1 472   263 GAG TTT CTG AGG ACA A  4509 AJ_P5 85653 H04 AJ_472 /5AmMC6/CCC AAT AGA CAG 10653 8755 61.9 473   264 GAC AGG TGT TCC CAA A  4510 AJ_P5 85653 H05 AJ_473 /5AmMC6/CCC AAT TCG GAA 10653 8687 58.8 474   265 GCC ATT TCT CTT AGA A  4511 AJ_P5 85653 H06 AJ_474 /5AmMC6/CCC AAT CGG AAC 10653 8672 60.3 475   266 AGT TCC TCA TTC TGA A  4512 AJ_P5 85653 H07 AJ_475 /5AmMC6/CCC AAT GAA GCA 10653 8696 59.2 476   267 GTT CCA TCA TTC TGA A  4513 AJ_P5 85653 H08 AJ_476 /5AmMC6/CCC AAC ATG TGT 10653 8737 61.9 477   268 CAA GGG TAG CTC TCA A  4514 AJ_P5 85653 H09 AJ_477 /5AmMC6/CCC AAG CCT TTA 10653 8666 62.8 478   269 CAC CAT GTG GAA CCA A  4515 AJ_P5 85653 H10 AJ_478 /5AmMC6/CCC AAC TAA CTG 10653 8786 61.5 479   270 CTG AGG TGA GGT ACA A  4516 AJ_P5 85653 H11 AJ_479 /5AmMC6/CCC AAC TCC AAG 10653 8746 61.9 480   271 TCG AGT GAG TTG ACA A  4517 AJ_P5 85653 H12 AJ_480 /5AmMC6/CCC AAC GAG TTG 10653 8779 60.3 481   272 AGA AGC TAC ATG ACA A  4518 AJ_P6  85653 A01 AJ_481 /5AmMC6/CCC AAT TTC TGA 10653 8721 60.2 482   274 GTG AGC AAC CCT AGA A  4519 AJ_P6  85653 A02 AJ_482 /5AmMC6/CCC AAG AGT ACA 10653 8675 60.8 483   275 GCT ACC TCT CCA AGA A  4520 AJ_P6  85653 A03 AJ_483 /5AmMC6/CCC AAG AGC ACT 10653 8699 60.4 484   276 CCA CTT GTA CAA AGA A  4521 AJ_P6  85653 A04 AJ_484 /5AmMC6/CCC AAG CTA CAT 10653 8687 58.3 485   277 TTC TTG AGT CGA CTA A  4522 AJ_P6  85653 A05 AJ_485 /5AmMC6/CCC AAA CCG TAG 10653 8699 60.2 486   278 GAC TAC AAC ACT TGA A  4523 AJ_P6  85653 A06 AJ_486 /5AmMC6/CCC AAA TTC CTG 10653 8752 60.8 487   279 TTG TGA CGA AGT CGA A  4524 AJ_P6  85653 A07 AJ_487 /5AmMC6/CCC AAA GTT CTG 10653 8752 60.8 488   280 TGG TTC ACA AGT CGA A  4525 AJ_P6  85653 A08 AJ_488 /5AmMC6/CCC AAG TAC TCG 10653 8672 59.8 489   281 AGT TCC CTT TAA CGA A  4526 AJ_P6  85653 A09 AJ_489 /5AmMC6/CCC AAG CTG AAG 10653 8763 59.3 490   282 GTT AAC AAC AAG CTA A  4527 AJ_P6  85653 A10 AJ_490 /5AmMC6/CCC AAT CGC ATG 10653 8723 59.8 491   283 GTA AAC AAA CAC TGA A  4528 AJ_P6  85653 A11 AJ_491 /5AmMC6/CCC AAC TGG TAC 10653 8699 61 492   284 TAA AGC CAA ACT GCA A  4529 AJ_P6  85653 A12 AJ_492 /5AmMC6/CCC AAC GTT AAG 10653 8730 59.4 493   285 AAG GTA CCT AGC CTA A  4530 AJ_P6  85653 B01 AJ_493 /5AmMC6/CCC AAC AGT GAA 10653 8721 60.6 494   286 AGT TGT CCT TCC AGA A  4531 AJ_P6  85653 B02 AJ_494 /5AmMC6/CCC AAC AGG AGT 10653 8786 61.4 495   287 TGG GTA CCA GTC TAA A  4532 AJ_P6  85653 B03 AJ_495 /5AmMC6/CCC AAG AAA CTG 10653 8699 61.1 496   288 TGC AAA CAC TCC TGA A  4533 AJ_P6  85653 B04 AJ_496 /5AmMC6/CCC AAT CGT AGT 10653 8690 60.1 497   289 TCG ACA AAC TCC AGA A  4534 AJ_P6  85653 B05 AJ_497 /5AmMC6/CCC AAC AGG TTA 10653 8666 62.1 498   290 GTT CAC ACC ATC CGA A  4535 AJ_P6  85653 B06 AJ_498 /5AmMC6/CCC AAG GTT TAC 10653 8657 61.7 499   291 GTC ACT CCA TCC AGA A  4536 AJ_P6  85653 B07 AJ_499 /5AmMC6/CCC AAG TTT AAC 10653 8687 59.3 500   292 CTC ATG CTT TAG CGA A  4537 AJ_P6  85653 B08 AJ_500 /5AmMC6/CCC AAT TTG TAC 10653 8672 60.9 501   293 GTT CCA ACC TAG GCA A  4538 AJ_P6  85653 B09 AJ_501 /5AmMC6/CCC AAA TCG TTT 10653 8727 59.8 502   294 GTT TCC AGT AGG CAA A  4539 AJ_P6  85653 B10 AJ_502 /5AmMC6/CCC AAG CAT CCT 10658 8672 60.7 503   295 TGT CTT AAC TGC AGA A  6458 AJ_P6  85653 B11 AJ_503 /5AmMC6/CCC AAA CTG GTA 10653 8697 62 504   296 AGT CTT GGC TAC CCA A  4541 AJ_P6  85653 B12 AJ_504 /5AmMC6/CCC AAG TCC ATG 10653 8675 63 505   297 TGC AAC ACC AAC TGA A  4542 AJ_P6 85653 C01 AJ_505 /5AmMC6/CCC AAG TCA CAG 10653 8675 61.7 506   298 GAC TCC TCA ACA TGA A  4543 AJ_P6 85653 C02 AJ_506 /5AmMC6/CCC AAG TAC TCT 10657 8672 60.1 507   299 CAT TCT GTG CAG ACA A  7185 AJ_P6 85653 C03 AJ_507 /5AmMC6/CCC AAG GTT CCA 10657 8657 62.6 508   300 CAC TTT GTC ACG ACA A  7186 AJ_P6 85653 C04 AJ_508 /5AmMC6/CCC AAA CTC GTC 10658 8681 60.1 509   301 TGT CCA TAA AGT CGA A  6459 AJ_P6 85653 C05 AJ_509 /5AmMC6/CCC AAC AAG GTG 10657 8712 60.6 510   302 TGT TCT ACC ATT CGA A  7187 AJ_P6 85653 C06 AJ_510 /5AmMC6/CCC AAA CTC GTG 10657 8736 58.6 511   303 TTG TAC TTA GAA CGA A  7188 AJ_P6 85653 C07 AJ_511 /5AmMC6/CCC AAA GGC ATT 10653 8723 59.9 512   304 GTC AAC AAA CCA GTA A  4549 AJ_P6 85653 C08 AJ_512 /5AmMC6/CCC AAC AGT AGT 10657 8736 58.5 513   305 TGT TAA CGA CTG CTA A  7189 AJ_P6 85653 C09 AJ_513 /5AmMC6/CCC AAT GCT CAG 10653 8723 59.1 514   306 GTC AAA CAA ACT AGA A  4551 AJ_P6 85653 C10 AJ_514 /5AmMC6/CCC AAT GTC GTA 10658 8727 58.3 515   307 CTT TGA GTA AGC CTA A  6460 AJ_P6 85653 C11 AJ_515 /5AmMC6/CCC AAG GCT AGA 10653 8739 60.2 516   308 CGA ACA TTA CCA TGA A  4553 AJ_P6 85653 C12 AJ_516 /5AmMC6/CCC AAC GAG TGT 10658 8752 60 517   309 TCT AGT GTT ACA CGA A  6461 AJ_P6 85653 D01 AJ_517 /5AmMC6/CCC AAC AGG TTT 10653 8752 60.3 518   310 ACG TGT GTA CAG CTA A  4555 AJ_P6 85653 D02 AJ_518 /5AmMC6/CCC AAA GGT TCC 10653 8672 60.6 519   311 TTC CAT GTA AGC TCA A  4556 AJ_P6 85653 D03 AJ_519 /5AmMC6/CCC AAA GGC TTT 10653 8727 59.3 520   312 GCT GTT ACT TAG ACA A  4557 AJ_P6 85653 D04 AJ_520 /5AmMC6/CCC AAC AAA GTA 10653 8745 59.9 521   313 ACT GTT CGT TGC GAA A  4558 AJ_P6 85653 D05 AJ_521 /5AmMC6/CCC AAA TGC TTG 10653 8696 59.1 522   314 GAA CTT CTA ACT CGA A  4559 AJ_P6 85653 D06 AJ_522 /5AmMC6/CCC AAC CTG AGT 10653 8721 60.4 523   315 ACT GTG CTC TGA AAA A  4560 AJ_P6 85653 D07 AJ_523 /5AmMC6/CCC AAG GAC TCA 10653 8657 61.6 524   316 AGT CTT CCT TCA CGA A  4561 AJ_P6 85653 D08 AJ_524 /5AmMC6/CCC AAA GGG TTC 10653 8721 60.7 525   317 CGT TCA CTA ACA TGA A  4562 AJ_P6 85653 D09 AJ_525 /5AmMC6/CCC AAC CAG TAC 10653 8712 60.5 526   318 TGC ATT TCT TGG AGA A  4563 AJ_P6 85653 D10 AJ_526 /5AmMC6/CCC AAC AAG CCT 10653 8712 60.5 527   319 AGT TCT GGT TGT ACA A  4564 AJ_P6 85653 D11 AJ_527 /5AmMC6/CCC AAC AGA CCT 10653 8672 60.5 528   320 ACC TTT GTT GTA GCA A  4565 AJ_P6 85653 D12 AJ_528 /5AmMC6/CCC AAG AAC CCT 10653 8681 60.9 529   321 TCT TTG ACT GCA AGA A  4566 AJ_P6 85653 E01 AJ_529 /5AmMC6/CCC AAA GTC GTT 10653 8672 60.2 530   322 TAG TCC TCT GAC CAA A  4567 AJ_P6 85653 E02 AJ_530 /5AmMC6/CCC AAA GTC TCT 10653 8712 60.2 531   323 TCG TTC AAC TGG AGA A  4568 AJ_P6 85653 E03 AJ_531 /5AmMC6/CCC AAC GCA TTC 10653 8714 58.6 532   324 TTA ACA GAG ACA GTA A  4569 AJ_P6 85653 E04 AJ_532 /5AmMC6/CCC AAC GAG TCT 10653 8770 59.4 533   325 CTT GAG AGG AAA CTA A  4570 AJ_P6 85653 E05 AJ_533 /5AmMC6/CCC AAC GTA GTG 10653 8755 61 534   326 AGT AGA CGT ACA CCA A  4571 AJ_P6 85653 E06 AJ_534 /5AmMC6/CCC AAA AAG CTT 10653 8696 59.6 535   327 GTT ACC TTC TGC AGA A  4572 AJ_P6 85653 E07 AJ_535 /5AmMC6/CCC AAA CTT TGT 10653 8745 59.1 536   328 ACT GGA GTA GCC AAA A  4573 AJ_P6 85653 E08 AJ_536 /5AmMC6/CCC AAG CTT ACC 10653 8705 58.9 537   329 TCT TAA GTG CAA GAA A  4574 AJ_P6 85653 E09 AJ_537 /5AmMC6/CCC AAG AAC CTC 10653 8723 58.9 538   330 TTA AAG CTA AGC GAA A  4575 AJ_P6 85653 E10 AJ_538 /5AmMC6/CCC AAG ACC TAA 10653 8739 60.4 539   331 ACA AGC TTG AGT CGA A  4576 AJ_P6 85653 E11 AJ_539 /5AmMC6/CCC AAT TTG CAT 10653 8687 59.5 540   332 AGG TTC TTC CAA CGA A  4577 AJ_P6 85653 E12 AJ_540 /5AmMC6/CCC AAG CAA GTT 10653 8672 61.1 541   333 GCA TTC CTC TCA TGA A  4578 AJ_P6 85653 F01 AJ_541 /5AmMC6/CCC AAT CGG TAC 10653 8739 59.9 542   334 ACG ACA TAC ATG AGA A  4579 AJ_P6 85653 F02 AJ_542 /5AmMC6/CCC AAA CCT CTG 10653 8712 60.2 543   335 TTT CTG AGT CGA AGA A  4580 AJ_P6 85653 F03 AJ_543 /5AmMC6/CCC AAA CAC GTG 10653 8745 59.3 544   336 TTG GCT AGT CTA AAA A  4581 AJ_P6 85653 F04 AJ_544 /5AmMC6/CCC AAC GGT TTA 10653 8672 61.3 545   337 AGC CTT TCA CCA TGA A  4582 AJ_P6 85653 F05 AJ_545 /5AmMC6/CCC AAC GGT TCA 10653 8786 61.7 546   338 TGG ACT AAC TGA GGA A  4583 AJ_P6 85653 F06 AJ_546 /5AmMC6/CCC AAA CCG TTC 10653 8721 61.4 547   339 AGT TTC ACA TGG GAA A  4584 AJ_P6 85653 F07 AJ_547 /5AmMC6/CCC AAG ACC TCT 10653 8657 61 548   340 CCA CTT GAC TGT AGA A  4585 AJ_P6 85653 F08 AJ_548 /5AmMC6/CCC AAG TCT TTA 10653 8712 59.7 549   341 CCT CAG TGT AGC AGA A  4586 AJ_P6 85653 F09 AJ_549 /5AmMC6/CCC AAA CAG CTG 10653 8690 60.2 550   342 AGT CCT TCC ATA AGA A  4587 AJ_P6 85653 F10 AJ_550 /5AmMC6/CCC AAA ACT GTC 10653 8672 60.6 551   343 ATT GCC TTC CTA GGA A  4588 AJ_P6 85653 F11 AJ_551 /5AmMC6/CCC AAG TCC ATT 10653 8712 60.6 552   344 CAT TCG TTC GAA GGA A  4589 AJ_P6 85653 F12 AJ_552 /5AmMC6/CCC AAG TCA CCT 10653 8737 61.6 553   345 CTT GGT AGT AAG GCA A  4590 AJ_P6 85653 G01 AJ_553 /5AmMC6/CCC AAC CAT CAG 10653 8712 60.9 554   346 CTT TAG TTG GTG ACA A  4591 AJ_P6 85653 G02 AJ_554 /5AmMC6/CCC AAG TTA CCT 10653 8666 61.7 555   347 GAC TCC ACT GGA CAA A  4592 AJ_P6 85653 G03 AJ_555 /5AmMC6/CCC AAA GTT GGC 10653 8727 60.1 556   348 ATC TTT GTC GTC AAA A  4593 AJ_P6 85653 G04 AJ_556 /5AmMC6/CCC AAA CGT TGT 10653 8687 59.4 557   349 GTC TTT AAC ATC CGA A  4594 AJ_P6 85653 G05 AJ_557 /5AmMC6/CCC AAC AGT TTG 10653 8712 61.5 558   350 GCT TTG ACA TCA CGA A  4595 AJ_P6 85653 G06 AJ_558 /5AmMC6/CCC AAA CGG TTT 10653 8687 60.1 559   351 GCA ACT CAT TCT TGA A  4596 AJ_P6 85653 G07 AJ_559 /5AmMC6/CCC AAG ACG ACT 10653 8672 59.8 560   352 GTT TAC TTC CTC AGA A  4597 AJ_P6 85653 G08 AJ_560 /5AmMC6/CCC AAG GAC TCC 10653 8657 61.9 561   353 ATT TCG ACT TCG ACA A  4598 AJ_P6 85653 G09 AJ_561 /5AmMC6/CCC AAA TCA AGT 10653 8763 58 562   354 CTA GAC AGA AGG CTA A  4599 AJ_P6 85653 G10 AJ_562 /5AmMC6/CCC AAG TCG TCA 10653 8699 60.4 563   355 TCA GCA AGA AAC CTA A  4600 AJ_P6 85653 G11 AJ_563 /5AmMC6/CCC AAT CGT GTA 10653 8754 59.1 564   356 CAT GGA AAG CAC ATA A  4601 AJ_P6 85653 G12 AJ_564 /5AmMC6/CCC AAC TTT GAA 10653 8754 59.1 565   357 GCA TGG AGA ACA CTA A  4602 AJ_P6 85653 H01 AJ_565 /5AmMC6/CCC AAA AGT CCT 10653 8727 58.6 566   358 CTG TTT AGT TAG CGA A  4603 AJ_P6 85653 H02 AJ_566 /5AmMC6/CCC AAG TAA CCA 10653 8699 60.5 567   359 AAC CAT GCT AGT CGA A  4604 AJ_P6 85653 H03 AJ_567 /5AmMC6/CCC AAG GAC ATT 10653 8675 62.4 568   360 GAC TCA CCA TCA GCA A  4605 AJ_P6 85653 H04 AJ_568 /5AmMC6/CCC AAT GGG TAC 10653 8730 60 569   361 TGC ATA CAC CAT AGA A  4606 AJ_P6 85653 H05 AJ_569 /5AmMC6/CCC AAA GAA CTC 10653 8696 58.8 570   362 GTC TTC ATT TAC GGA A  4607 AJ_P6 85653 H06 AJ_570 /5AmMC6/CCC AAA GGT CTT 10653 8752 59.5 571   363 TGT CCT AGT ACG AGA A  4608 AJ_P6 85653 H07 AJ_571 /5AmMC6/CCC AAC ATG GTT 10653 8770 60.3 572   364 AAG GTC AAC TCG AGA A  4609 AJ_P6 85653 H08 AJ_572 /5AmMC6/CCC AAG CTT GTA 10653 8672 59.9 573   365 ACG ACT TAC TCT CGA A  4610 AJ_P6 85653 H09 AJ_573 /5AmMC6/CCC AAG ACC ACT 10653 8657 61.7 574   366 CTC CTA GCA TTT GGA A  4611 AJ_P6 85653 H10 AJ_574 /5AmMC6/CCC AAG TCC ATT 10653 8697 62.2 575   367 CCC ATT GGT AGC AGA A  4612 AJ_P6 85653 H11 AJ_575 /5AmMC6/CCC AAC ACT CTG 10653 8737 61.3 576   368 TGT CGT ACA TAG GGA A  4613 AJ_P6 85653 H12 AJ_576 /5AmMC6/CCC AAA CTT GTG 10653 8706 62.8 577   369 TGG AAA CCG TAC CCA A  4614 AJ_P7 85653 A01 AJ_577 /5AmMC6/CCC AAA TGC CTT 10653 8761 61 578   371 GGT GTC ATA CAG GAA A  4711 AJ_P7 85653 A02 AJ_578 /5AmMC6/CCC AAT CGG AAG 10653 8763 57.8 579   372 TCA GAC TAG AAA CTA A  4712 AJ_P7 85653 A03 AJ_579 /5AmMC6/CCC AAC CAG TAC 10653 8755 61 580   373 CAG AGG TGA AGT CTA A  4713 AJ_P7 85653 A04 AJ_580 /5AmMC6/CCC AAC ATA AAG 10653 8763 58.4 581   374 GGA AAC TGA GCT CTA A  4714 AJ_P7 85653 A05 AJ_581 /5AmMC6/CCC AAC TAA GAG 10653 8779 59.6 582   375 GAG AAC TCC AGT TGA A  4715 AJ_P7 85653 A06 AJ_582 /5AmMC6/CCC AAC TAG GAA 10653 8681 59.5 583   376 GTT TAC TCC ACT CGA A  4716 AJ_P7 85653 A07 AJ_583 /5AmMC6/CCC AAC AAC GTC 10653 8730 60.3 584   377 TGC TAA AGT AGG TCA A  4717 AJ_P7 85653 A08 AJ_584 /5AmMC6/CCC AAC GTC ATC 10653 8714 58.4 585   378 AAC ATA GTA GGC TAA A  4718 AJ_P7 85653 A09 AJ_585 /5AmMC6/CCC AAA TCG TCA 10653 8763 57.3 586   379 CTA GAG AGA GAA CTA A  4719 AJ_P7 85653 A10 AJ_586 /5AmMC6/CCC AAC TTG TCA 10653 8730 60 587   380 CAT GAA GGA GAC CTA A  4720 AJ_P7 85653 A11 AJ_587 /5AmMC6/CCC AAG GAG ACT 10653 8739 59.5 588   381 CTA GAA ACT TCC GAA A  4721 AJ_P7 85653 A12 AJ_588 /5AmMC6/CCC AAG AGT TAC 10653 8672 59.7 589   382 GCT TCT ACT TCC AGA A  4722 AJ_P7 85653 B01 AJ_589 /5AmMC6/CCC AAA CCA GTC 10653 8746 61.5 590   383 CTT AAG GGT AGG TCA A  4723 AJ_P7 85653 B02 AJ_590 /5AmMC6/CCC AAA AGC CTA 10653 8723 58.8 591   384 GAA CAT TAC ATC GGA A  4724 AJ_P7 85653 B03 AJ_591 /5AmMC6/CCC AAG CTG AAA 10653 8690 61.1 592   385 GCA CTC CAT CAT TGA A  4725 AJ_P7 85653 B04 AJ_592 /5AmMC6/CCC AAT CAG TGT 10653 8657 61.1 593   386 GAC TCC ATC CCT AGA A  4726 AJ_P7 85653 B05 AJ_593 /5AmMC6/CCC AAG CTA CTT 10653 8687 58.6 594   387 AAC TCT GTT TCG GAA A  4727 AJ_P7 85653 B06 AJ_594 /5AmMC6/CCC AAA TGC TTT 10653 8752 60.6 595   388 CAC TGG TCT AGG GAA A  4728 AJ_P7 85653 B07 AJ_595 /5AmMC6/CCC AAC AGT TGT 10653 8712 60.9 596   389 TCG TTC ATG ACC AGA A  4729 AJ_P7 85653 B08 AJ_596 /5AmMC6/CCC AAT CAC GAA 10653 8739 59.8 597   390 ACG ACT ACT TAG GGA A  4730 AJ_P7 85653 B09 AJ_597 /5AmMC6/CCC AAC ATT GTT 10653 8727 60.1 598   391 TGG TTC ATC AAG CGA A  4731 AJ_P7 85653 B10 AJ_598 /5AmMC6/CCC AAA TTC TTG 10653 8736 59.8 599   392 TGG TAC AAC ATG CGA A  4732 AJ_P7 85653 B11 AJ_599 /5AmMC6/CCC AAC CTG ACC 10653 8672 61 600   393 AAC GGT TCA TTT GTA A  4733 AJ_P7 85653 B12 AJ_600 /5AmMC6/CCC AAG ACC ATT 10653 8672 60.8 601   394 ACG TCT TGC CTT GAA A  4734 AJ_P7 85653 C01 AJ_601 /5AmMC6/CCC AAG CCA TAC 10653 8672 60.8 602   395 CTC ATT GAG CTT TGA A  4735 AJ_P7 85653 C02 AJ_602 /5AmMC6/CCC AAA GGA CTC 10653 8657 61.7 603   396 TTC CGT AAC CTG TCA A  4736 AJ_P7 85653 C03 AJ_603 /5AmMC6/CCC AAG GAG TGC 10653 8761 60.8 604   397 ATT TCG TAA CCT GAA A  4737 AJ_P7 85653 C04 AJ_604 /5AmMC6/CCC AAT CAC AAG 10653 8754 58.6 605   398 CGA AAG TAG TGT CTA A  4738 AJ_P7 85653 C05 AJ_605 /5AmMC6/CCC AAT CGA AGA 10653 8770 60.1 606   399 GAC GAC TTG AGT TCA A  4739 AJ_P7 85653 C06 AJ_606 /5AmMC6/CCC AAA TGG CTT 10653 8761 61.2 607   400 TGG TAC AAC TGA CGA A  4740 AJ_P7 85653 C07 AJ_607 /5AmMC6/CCC AAG AGA CGT 10653 8755 61.6 608   401 TGG AAC ACC TAC TGA A  4741 AJ_P7 85653 C08 AJ_608 /5AmMC6/CCC AAG AAA GCT 10653 8699 61.1 609   402 GTT CAA ACC TCA CGA A  4742 AJ_P7 85653 C09 AJ_609 /5AmMC6/CCC AAG TGA GTC 10653 8761 60.4 610  403 TTC GAA ACT TCG GAA A  4743 AJ_P7 85653 C10 AJ_610 /5AmMC6/CCC AAC CAG TGT 10653 8786 62.4 611   404 TAA CGG AAC TTG GGA A  4744 AJ_P7 85653 C11 AJ_611 /5AmMC6/CCC AAC AGG TGT 10653 8777 61.3 612   405 ACT TGG TAC TAC GGA A  4745 AJ_P7 85653 C12 AJ_612 /5AmMC6/CCC AAG TAC CAT 10653 8672 59.8 613   406 CCT TAC GTA GCT TGA A  4746 AJ_P7 85653 D01 AJ_613 /5AmMC6/CCC AAG CTA CTT 10653 8706 60.9 614   407 CCA CTA GGT ACA GGA A  4747 AJ_P7 85653 D02 AJ_614 /5AmMC6/CCC AAG TAC CTC 10653 8699 60.1 615   408 AAC AAG TCA AGG CTA A  4748 AJ_P7 85653 D03 AJ_615 /5AmMC6/CCC AAG TAC CCA 10653 8739 59.8 616   409 AGA GAC TAA GCT TGA A  4749 AJ_P7 85653 D04 AJ_616 /5AmMC6/CCC AAT GAA CCA 10653 8699 61 617   410 AAC ACT GAC CTG TGA A  4750 AJ_P7 85653 D05 AJ_617 /5AmMC6/CCC AAG TGC ACA 10653 8699 60.8 618   411 TCG AAC CAA CTT AGA A  4751 AJ_P7 85653 D06 AJ_618 /5AmMC6/CCC AAT GCT TAG 10653 8696 58.2 619   412 CGT ACT ACC ATT AGA A  4752 AJ_P7 85653 D07 AJ_619 /5AmMC6/CCC AAG TTT GAC 10653 8681 61.2 620   413 GTT CAA CCA TCA CGA A  4753 AJ_P7 85653 D08 AJ_620 /5AmMC6/CCC AAT TTA GCT 10653 8712 60.2 621   414 TGT CCA CTC AGA GGA A  4754 AJ_P7 85653 D09 AJ_621 /5AmMC6/CCC AAC GCT ACT 10653 8687 58.4 622   415 TTC TTA GTT AGA GCA A  4755 AJ_P7 85653 D10 AJ_622 /5AmMC6/CCC AAA AGC CTT 10653 8672 60.9 623   416 TCC ACT GTT ACT GGA A  4756 AJ_P7 85653 D11 AJ_623 /5AmMC6/CCC AAC CTG TTA 10653 8697 61.9 624   417 CCT CAG ACA TTG GGA A  4757 AJ_P7 85653 D12 AJ_624 /5AmMC6/CCC AAC GTC ATT 10653 8752 59.6 625   418 TAG GTC TCT AAG GGA A  4758 AJ_P7 85653 E01 AJ_625 /5AmMC6/CCC AAA CGT CTT 10653 8712 60.2 626   419 GGG TTA CAC TAC TGA A  4759 AJ_P7 85653 E02 AJ_626 /5AmMC6/CCC AAT CAC AGA 10653 8690 60.8 627   420 ACC AGT CAG CTT TGA A  4760 AJ_P7 85653 E03 AJ_627 /5AmMC6/CCC AAG TGG TAC 10653 8697 60.9 628   421 TCT CGT AAC TCC AGA A  4761 AJ_P7 85653 E04 AJ_628 /5AmMC6/CCC AAG AAC TCC 10653 8675 61.2 629   422 TAC CAA GAC TCG TGA A  4762 AJ_P7 85653 E05 AJ_629 /5AmMC6/CCC AAT TTG ACT 10653 8705 59.7 630   423 TGA ACG CAT AAC CGA A  4763 AJ_P7 85653 E06 AJ_630 /5AmMC6/CCC AAT TGA GAC 10653 8699 59.8 631   424 CTC ACG AGA ACA CTA A  4764 AJ_P7 85653 E07 AJ_631 /5AmMC6/CCC AAA CAA AGT 10653 8745 59.8 632   425 CAT TGG GTT CGC TAA A  4765 AJ_P7 85653 E08 AJ_632 /5AmMC6/CCC AAT CGA ACA 10653 8699 60.4 633   426 AAC CTA GAG TGC TCA A  4766 AJ_P7 85653 E09 AJ_633 /5AmMC6/CCC AAG GTC TTA 10653 8681 59.8 634   427 GCT ACA ACC TCA TGA A  4767 AJ_P7 85653 E10 AJ_634 /5AmMC6/CCC AAG CTT TGA 10653 8681 60.7 635   428 AGC CTT CCA ACT AGA A  4768 AJ_P7 85653 E11 AJ_635 /5AmMC6/CCC AAT ACA GGT 10653 8699 60.5 636   429 GTC ACA AAC TCA CGA A  4769 AJ_P7 85653 E12 AJ_636 /5AmMC6/CCC AAC CGT TCA 10653 8699 60.4 637   430 TAA CAA GGG AAC CTA A  4770 AJ_P7 85653 F01 AJ_637 /5AmMC6/CCC AAA GTA CCC 10653 8739 61 638   431 AAA GCA TGT CTG GAA A  4771 AJ_P7 85653 F02 AJ_638 /5AmMC6/CCC AAA TGT TCT 10653 8727 58.8 639   432 CTT TAC GCT AGG GAA A  4772 AJ_P7 85653 F03 AJ_639 /5AmMC6/CCC AAT TTG ACT 10653 8745 59.3 640   433 TCA GAC GAA AGC TGA A  4773 AJ_P7 85653 F04 AJ_640 /5AmMC6/CCC AAT ACA GAA 10653 8723 59 641   434 ACG ACA TAC GCT TGA A  4774 AJ_P7 85653 F05 AJ_641 /5AmMC6/CCC AAT CAC CAG 10653 8699 60 642   435 AAG AAC TAC CTG TGA A  4775 AJ_P7 85653 F06 AJ_642 /5AmMC6/CCC AAT ACG AAC 10653 8770 60.2 643   436 GAC AGG TCA TGG TTA A  4776 AJ_P7 85653 F07 AJ_643 /5AmMC6/CCC AAG AAC TCC 10653 8690 59.9 644   437 AAC CAT GTA GTC GTA A  4777 AJ_P7 85653 F08 AJ_644 /5AmMC6/CCC AAA TTG CGT 10653 8696 59.6 645   438 TCT TCA GTA CAC GAA A  4778 AJ_P7 85653 F09 AJ_645 /5AmMC6/CCC AAA TCT GCT 10653 8672 60 646   439 TCC TGT AGT ACA CGA A  4779 AJ_P7 85653 F10 AJ_646 /5AmMC6/CCC AAG GTC ACT 10653 8675 62.3 647   440 TGC AAC CTA GAA CCA A  4780 AJ_P7 85653 F11 AJ_647 /5AmMC6/CCC AAG GCT TAG 10653 8715 61.5 648   441 TAC GAC AGT AAC CCA A  4781 AJ_P7 85653 F12 AJ_648 /5AmMC6/CCC AAC AAG TGA 10653 8795 62 649   442 AGT GGT CTG ACC AGA A  4782 AJ_P7 85653 G01 AJ_649 /5AmMC6/CCC AAC AGA GTA 10653 8770 59.3 650   443 GTG TGA CTA GCC TAA A  4783 AJ_P7 85653 G02 AJ_650 /5AmMC6/CCC AAT CAC AAG 10653 8754 59.1 651   444 GAG TAG CAA CTT TGA A  4784 AJ_P7 85653 G03 AJ_651 /5AmMC6/CCC AAC CTG TAA 10653 8779 60.5 652   445 GTG AAA CGA CTG GAA A  4785 AJ_P7 85653 G04 AJ_652 /5AmMC6/CCC AAC CCT AGT 10653 8755 61.8 653   446 TGA GGA CAA ACT GGA A  4786 AJ_P7 85653 G05 AJ_653 /5AmMC6/CCC AAG GCA TCA 10653 8690 60.8 654   447 CAC CTA GCA AGT TTA A  4787 AJ_P7 85653 G06 AJ_654 /5AmMC6/CCC AAG ACC TAC 10653 8666 60.9 655   448 CCT ACA GAG CTT GTA A  4788 AJ_P7 85653 G07 AJ_655 /5AmMC6/CCC AAT TTC GTA 10653 8736 59.1 656   449 ACA AGT TGG ACT CGA A  4789 AJ_P7 85653 G08 AJ_656 /5AmMC6/CCC AAT CAA AGA 10653 8763 59.8 657   450 AAC AGG TTG CAC TGA A  4790 AJ_P7 85653 G09 AJ_657 /5AmMC6/CCC AAC GTC TTA 10653 8657 61.7 658   451 GAG TCC TTG AAC CCA A  4791 AJ_P7 85653 G10 AJ_658 /5AmMC6/CCC AAT GCT GAA 10653 8687 59.8 659   452 ACG TTT CCC TTG TAA A  4792 AJ_P7 85653 G11 AJ_659 /5AmMC6/CCC AAC AGG TTT 10653 8752 60.8 660   453 GTT TGA CTC AGA CGA A  4793 AJ_P7 85653 G12 AJ_660 /5AmMC6/CCC AAC CTT CGA 10653 8723 59 661   454 CAT AAA GAA AGC GTA A  4794 AJ_P7 85653 H01 AJ_661 /5AmMC6/CCC AAT GAA CCA 10653 8763 59.4 662   455 TTA GCA AGC AAG GTA A  4795 AJ_P7 85653 H02 AJ_662 /5AmMC6/CCC AAT GAA CCT 10653 8739 61.3 663   456 TGA GCA CAA ACT GGA A  4796 AJ_P7 85653 H03 AJ_663 /5AmMC6/CCC AAA GGG TTC 10653 8737 61.8 664   457 TTG GAC AGT ACC TCA A  4797 AJ_P7 85653 H04 AJ_664 /5AmMC6/CCC AAC TGT AAA 10653 8721 59.5 665   458 GGA GTT CGT ACC CTA A  4798 AJ_P7 85653 H05 AJ_665 /5AmMC6/CCC AAT CGA GAA 10653 8779 59.8 666   459 GGA AGT CAC ACT GTA A  4799 AJ_P7 85653 H06 AJ_666 /5AmMC6/CCC AAC TAA AGG 10653 8770 60.4 667   460 AAG TGT CAG CTG TCA A  4800 AJ_P7 85653 H07 AJ_667 /5AmMC6/CCC AAG CAC ATA 10653 8779 61.1 668   461 AGG TCA AAC GTG TGA A  4801 AJ_P7 85653 H08 AJ_668 /5AmMC6/CCC AAC GTT GAA 10653 8779 61 669   462 GGA ACA TTC ACA GGA A  4802 AJ_P7 85653 H09 AJ_669 /5AmMC6/CCC AAT GTG AGC 10653 8763 59.8 670   463 TGA CAA ACA ACA TGA A  4803 AJ_P7 85653 H10 AJ_670 /5AmMC6/CCC AAG CTA CTC 10653 8675 61.4 671   464 TAA CAC GAC TGG ACA A  4804 AJ_P7 85653 H11 AJ_671 /5AmMC6/CCC AAG CCT AAC 10653 8681 60.8 672   465 CTT CAA GTG CAT GTA A  4805 AJ_P7 85653 H12 AJ_672 /5AmMC6/CCC AAG TAA ACA 10653 8730 59.9 673   466 CCT CTA GGT TCG GAA A  4806 AJ_P8 85653 A01 AJ_673 /5AmMC6/CCC AAG TCT TGA 10653 8681 60 674   468 CTC TCG ACT CGA AAA A  4807 AJ_P8 85653 A02 AJ_674 /5AmMC6/CCC AAC TGC AGA 10653 8779 61.1 675   469 GTG GAC TTG ACA AAA A  4808 AJ_P8 85653 A03 AJ_675 /5AmMC6/CCC AAC AGC TCT 10653 8721 60 676   470 GGT GTA CTT AAG ACA A  4809 AJ_P8 85653 A04 AJ_676 /5AmMC6/CCC AAT ACG AGA 10653 8779 59.6 677   471 GAG ACG TTT ACG ACA A  4810 AJ_P8 85653 A05 AJ_677 /5AmMC6/CCC AAG TAC CCT 10653 8666 60.9 678   472 ACT CTC GTC AAG GAA A  4811 AJ_P8 85653 A06 AJ_678 /5AmMC6/CCC AAT AAC GAC 10653 8699 60.5 679   473 ACA ACT GGT TAC CGA A  4812 AJ_P8 85653 A07 AJ_679 /5AmMC6/CCC AAC ACG TCA 10653 8675 61.5 680   474 TAA CGG TAG ACC TCA A  4813 AJ_P8 85653 A08 AJ_680 /5AmMC6/CCC AAT CCC AAG 10653 8699 60.2 681   475 CAA CAG TCA GTA GTA A  4814 AJ_P8 85653 A09 AJ_681 /5AmMC6/CCC AAT AAA CGA 10653 8699 60.8 682   476 ACA CCT GTG AGC TCA A  4815 AJ_P8 85653 A10 AJ_682 /5AmMC6/CCC AAG TTA CCA 10653 8699 60.2 683   477 GAC TCA ACA ACG GTA A  4816 AJ_P8 85653 A11 AJ_683 /5AmMC6/CCC AAG TTA GCT 10653 8690 60.8 684   478 TGA CCA ACC AAC GTA A  4817 AJ_P8 85653 A12 AJ_684 /5AmMC6/CCC AAG ACC ATC 10653 8675 60.7 685   479 ACT ACA GGA GTC CTA A  4818 AJ_P8 85653 B01 AJ_685 /5AmMC6/CCC AAG TAC TCT 10653 8712 59.3 686   480 TCT TAC GGT AGC AGA A  4819 AJ_P8 85653 B02 AJ_686 /5AmMC6/CCC AAT TTG CCA 10653 8714 60.4 687   481 TCG ACA ACG TGA AAA A  4820 AJ_P8 85653 B03 AJ_687 /5AmMC6/CCC AAA GTC TCT 10653 8752 60.2 688   482 TGG GTA CAA CGT GTA A  4821 AJ_P8 85653 B04 AJ_688 /5AmMC6/CCC AAT GAC CTT 10653 8672 60.2 689   483 CTC GTT ACA ACG GTA A  4822 AJ_P8 85653 B05 AJ_689 /5AmMC6/CCC AAT ACC GTT 10653 8736 58.6 690   484 CTG TTA AGA AGC GTA A  4823 AJ_P8 85653 B06 AJ_690 /5AmMC6/CCC AAA GTC CTT 10653 8672 59.6 691   485 CCT CTA GTT ACG GAA A  4824 AJ_P8 85653 B07 AJ_691 /5AmMC6/CCC AAG CCA TAC 10653 8730 60.6 692   486 AAC ATT GGA CTG GTA A  4825 AJ_P8 85653 B08 AJ_692 /5AmMC6/CCC AAC CTG AGA 10653 8761 59.8 693   487 GGT AAG CTT GAC TTA A  4826 AJ_P8 85653 B09 AJ_693 /5AmMC6/CCC AAC ACC TAG 10653 8746 61.2 694   488 TAG TCG TTG GAC AGA A  4827 AJ_P8 85653 B10 AJ_694 /5AmMC6/CCC AAG TAC ACT 10653 8723 59.6 695   489 AAA CCG TTG CGA AAA A  4828 AJ_P8 85653 B11 AJ_695 /5AmMC6/CCC AAC CAC TGG 10653 8730 60.8 696   490 TAC GGA AAG CTT TAA A  4829 AJ_P8 85653 B12 AJ_696 /5AmMC6/CCC AAG ACC ACT 10653 8746 61.2 697   491 CTT TGA GGA GTA CGA A  4830 AJ_P8 85653 C01 AJ_697 /5AmMC6/CCC AAG ACT GAC 10653 8795 62 698   492 CTT GGA AAG TAG GCA A  4831 AJ_P8 85653 C02 AJ_698 /5AmMC6/CCC AAC TCA CGT 10653 8739 60 699   493 TAC GAA ACA GAG GTA A  4832 AJ_P8 85653 C03 AJ_699 /5AmMC6/CCC AAG CGT AAC 10653 8687 59.2 700   494 GTC ATT TAC TTT CGA A  4833 AJ_P8 85653 C04 AJ_700 /5AmMC6/CCC AAC GAA CGT 10653 8687 59.7 701   495 GTC ATT TCA CTT TGA A  4834 AJ_P8 85653 C05 AJ_701 /5AmMC6/CCC AAA TCT CTG 10653 8657 62.1 702   496 GTG TCC ATC CGA ACA A  4835 AJ_P8 85653 C06 AJ_702 /5AmMC6/CCC AAA GCT TTG 10653 8761 61.1 703   497 GAG TCT GTG ACA ACA A  4836 AJ_P8 85653 C07 AJ_703 /5AmMC6/CCC AAG GGT ACT 10653 8786 61.9 704   498 AGG CTT GTG ACA ACA A  4837 AJ_P8 85653 C08 AJ_704 /5AmMC6/CCC AAT AGC GAA 10653 8699 60 705   499 CAC CTA GTT ACG ACA A  4838 AJ_P8 85653 C09 AJ_705 /5AmMC6/CCC AAT CAC GAG 10653 8675 61.7 706   500 TCC AAG AGT TAC CCA A  4839 AJ_P8 85653 C10 AJ_706 /5AmMC6/CCC AAT GAG AAC 10653 8763 59.1 707   501 AAA GGC TAA CCG TTA A  4840 AJ_P8 85653 C11 AJ_707 /5AmMC6/CCC AAC TCG TCA 10653 8699 59.9 708   502 TAG AAC ACC AAG GTA A  4841 AJ_P8 85653 C12 AJ_708 /5AmMC6/CCC AAC TCC ATG 10653 8723 59 709   503 CAA GTA AAG AAC GTA A  4842 AJ_P8 85653 D01 AJ_709 /5AmMC6/CCC AAA TGT GAC 10653 8705 59.3 710   504 TAC CGA AAC GCT TTA A  4843 AJ_P8 85653 D02 AJ_710 /5AmMC6/CCC AAG ACA AGT 10653 8699 60.8 711   505 TGA CCA ACG CAT CTA A  4844 AJ_P8 85653 D03 AJ_711 /5AmMC6/CCC AAC TGC ACA 10653 8690 60.5 712   506 GTT TAC AAC CTA GGA A  4845 AJ_P8 85653 D04 AJ_712 /5AmMC6/CCC AAG CTG ACT 10653 8672 59.8 713   507 GTC TTA ACC CTT AGA A  4846 AJ_P8 85653 D05 AJ_713 /5AmMC6/CCC AAG GTC AAG 10653 8739 60 714   508 TCG ACA AGC TAA CTA A  4847 AJ_P8 85653 D06 AJ_714 /5AmMC6/CCC AAC ACG TGA 10653 8675 62 715   509 GTT CCA ACC CTA AGA A  4848 AJ_P8 85653 D07 AJ_715 /5AmMC6/CCC AAG CCA TAA 10653 8690 59.9 716   510 CCA TCA GTC TGA GTA A  4849 AJ_P8 85653 D08 AJ_716 /5AmMC6/CCC AAG TCA ACA 10653 8699 60 717   511 CAC TCA GCA GTA GTA A  4850 AJ_P8 85653 D09 AJ_717 /5AmMC6/CCC AAG TAC CTA 10653 8672 60 718   512 CTC ATG CTT GCA GTA A  4851 AJ_P8 85653 D10 AJ_718 /5AmMC6/CCC AAA TGT ACG 10653 8723 59.2 719   513 TAA AGC ACA AGC CTA A  4852 AJ_P8 85653 D11 AJ_719 /5AmMC6/CCC AAC GTG TAA 10653 8779 60 720   514 AGG AAC TAG GCT ACA A  4853 AJ_P8 85653 D12 AJ_720 /5AmMC6/CCC AAG GTC ACT 10653 8675 61.4 721   515 AAC TCA GGA ACT CCA A  4854 AJ_P8 85653 E01 AJ_721 /5AmMC6/CCC AAT TCG AAG 10653 8723 59.4 722   516 TAA GCA ACA CCA TGA A  4855 AJ_P8 85653 E02 AJ_722 /5AmMC6/CCC AAT CGG AAG 10653 8779 60.6 723   517 TGT AAA CTG GAC ACA A  4856 AJ_P8 85653 E03 AJ_723 /5AmMC6/CCC AAG ACT CAC 10653 8690 60.2 724   518 AAA CCG TAC TTG GTA A  4857 AJ_P8 85653 E04 AJ_724 /5AmMC6/CCC AAC ATT CTG 10653 8770 60.2 725   519 CAT AGG AGA CAG TGA A  4858 AJ_P8 85653 E05 AJ_725 /5AmMC6/CCC AAA CCC ATG 10653 8699 61.3 726   520 CAC ATT GAG AAC TGA A  4859 AJ_P8 85653 E06 AJ_726 /5AmMC6/CCC AAT GGT CAG 10653 8739 59.7 727   521 GAC TAA ACT ACC AGA A  4860 AJ_P8 85653 E07 AJ_727 /5AmMC6/CCC AAG CTT CCA 10653 8712 60.6 728   522 GAA CTT TAC TTG GGA A  4861 AJ_P8 85653 E08 AJ_728 /5AmMC6/CCC AAG TTC AAC 10653 8675 62.3 729   523 TCC AAC GTC AGG ACA A  4862 AJ_P8 85653 E09 AJ_729 /5AmMC6/CCC AAG TTA CTA 10653 8681 59.4 730   524 CCA TAC GAC TCG TGA A  4863 AJ_P8 85653 E10 AJ_730 /5AmMC6/CCC AAC AGA CAT 10653 8699 60.5 731   525 GCA CTT AAC TCA GGA A  4864 AJ_P8 85653 E11 AJ_731 /5AmMC6/CCC AAC TTG AAC 10653 8779 60.2 732   526 CTA GAA AGG GTA GCA A  4865 AJ_P8 85653 E12 AJ_732 /5AmMC6/CCC AAG TCC TAC 10653 8730 58.8 733   527 CTT AAG AGA CGA GTA A  4866 AJ_P8 85653 F01 AJ_733 /5AmMC6/CCC AAC AGT TAG 10653 8761 61.1 734   528 GGA AGC TTT GCA TCA A  4867 AJ_P8 85653 F02 AJ_734 /5AmMC6/CCC AAC GTC TAG 10653 8745 58.2 735   529 CTA GAA GAA GTT TCA A  4868 AJ_P8 85653 F03 AJ_735 /5AmMC6/CCC AAT TTA GTC 10653 8672 60 736   530 ACC TCT GGA ACC GTA A  4869 AJ_P8 85653 F04 AJ_736 /5AmMC6/CCC AAC AGT GAA 10653 8730 60.9 737   531 GGA ACC TTT CGT CAA A  4870 AJ_P8 85653 F05 AJ_737 /5AmMC6/CCC AAA GGC TTC 10653 8687 59.1 738   532 CTT TCA GAC AGT TTA A  4871 AJ_P8 85653 F06 AJ_738 /5AmMC6/CCC AAA CGG TTG 10653 8761 60.9 739   533 TTG AGT CGA ACC ATA A  4872 AJ_P8 85653 F07 AJ_739 /5AmMC6/CCC AAA CCT CTG 10653 8730 60.5 740   534 AGT TGG CTA AAC AGA A  4873 AJ_P8 85653 F08 AJ_740 /5AmMC6/CCC AAG CAG TTG 10653 8779 60.3 741   535 TAA GAC CAA GAC GTA A  4874 AJ_P8 85653 F09 AJ_741 /5AmMC6/CCC AAG AGA GCT 10653 8727 58.6 742   536 ACC GTT TCT TTG TAA A  4875 AJ_P8 85653 F10 AJ_742 /5AmMC6/CCC AAA GGG TTC 10653 8761 60.4 743   537 TCC AAG TTT ACA GGA A  4876 AJ_P8 85653 F11 AJ_743 /5AmMC6/CCC AAC GTT AGT 10653 8727 59.6 744   538 GTG TTC AAG CTT CAA A  4877 AJ_P8 85653 F12 AJ_744 /5AmMC6/CCC AAC TCA CTG 10653 8739 60.8 745   539 CAA AGG TAA AGG TCA A  4878 AJ_P8 85653 G01 AJ_745 /5AmMC6/CCC AAG AGC TCA 10653 8786 61.9 746   540 CAA GGT GTT AGG TCA A  4879 AJ_P8 85653 G02 AJ_746 /5AmMC6/CCC AAC TGT CTA 10653 8752 60.4 747   541 CTG AAG GAG TTT GCA A  4880 AJ_P8 85653 G03 AJ_747 /5AmMC6/CCC AAA GCT TCC 10653 8687 58.3 748   542 TTT ACT GAC TAG TGA A  4881 AJ_P8 85653 G04 AJ_748 /5AmMC6/CCC AAC TGC TAC 10653 8681 60.1 749   543 CCT TGA GTA AAG TCA A  4882 AJ_P8 85653 G05 AJ_749 /5AmMC6/CCC AAG CTC ATT 10653 8681 60.2 750   544 CCC TTG AAC AGA GTA A  4883 AJ_P8 85653 G06 AJ_750 /5AmMC6/CCC AAG AGA CTG 10653 8715 61.9 751   545 TGC ACA ACC CTT AGA A  4884 AJ_P8 85653 G07 AJ_751 /5AmMC6/CCC AAC GGT TAA 10653 8714 59.4 752   546 CCT CAA GTG CTA AAA A  4885 AJ_P8 85653 G08 AJ_752 /5AmMC6/CCC AAA CCC TTG 10653 8755 61.7 753   547 GGT AAG CTA GAG ACA A  4886 AJ_P8 85653 G09 AJ_753 /5AmMC6/CCC AAA TTG CTC 10653 8672 61.2 754   548 ACG TTC TCA TGG ACA A  4887 AJ_P8 85653 G10 AJ_754 /5AmMC6/CCC AAC CCT AGG 10653 8690 60.3 755   549 AAG CCA TCA GTT TAA A  4888 AJ_P8 85653 G11 AJ_755 /5AmMC6/CCC AAA CCG TTT 10653 8672 61.3 756   550 GAA CCT TCT GGT CAA A  4889 AJ_P8 85653 G12 AJ_756 /5AmMC6/CCC AAT CCG AAG 10653 8739 60.7 757   551 GAG AAC TTT GAC CAA A  4890 AJ_P8 85653 H01 AJ_757 /5AmMC6/CCC AAT TGA GTC 10653 8754 59.1 758   552 TGA AGC AAC CAA GTA A  4891 AJ_P8 85653 H02 AJ_758 /5AmMC6/CCC AAC TGT TTA 10653 8727 58.7 759   553 GAG TGA CAT TGC CTA A  4892 AJ_P8 85653 H03 AJ_759 /5AmMC6/CCC AAT ACT GTT 10653 8705 58.5 760   554 AAG GCT ACA ACG CTA A  4893 AJ_P8 85653 H04 AJ_760 /5AmMC6/CCC AAA TCG GTT 10653 8672 60.1 761   555 CGT TCA CTA CTC AGA A  4894 AJ_P8 85653 H05 AJ_761 /5AmMC6/CCC AAC CAA GGT 10653 8737 62 762   556 TGG CTT AGT AGT CCA A  4895 AJ_P8 85653 H06 AJ_762 /5AmMC6/CCC AAG GCT ACA 10653 8672 60.6 763   557 GAC TTT CCC ATT TGA A  4896 AJ_P8 85653 H07 AJ_763 /5AmMC6/CCC AAG AAC CTC 10653 8712 61 764   558 ACG TGT GCT TGT TAA A  4897 AJ_P8 85653 H08 AJ_764 /5AmMC6/CCC AAG ACA TCC 10653 8672 60.5 765   559 ACT CTT GTT TGA CGA A  4898 AJ_P8 85653 H09 AJ_765 /5AmMC6/CCC AAG GTA CAC 10653 8657 62.2 766   560 ACC TTT GCC TTA CGA A  4899 AJ_P8 85653 H10 AJ_766 /5AmMC6/CCC AAC GAG TTG 10653 8779 60.1 767   561 GAG TAA CAT ACG ACA A  4900 AJ_P8 85653 H11 AJ_767 /5AmMC6/CCC AAA CGG TTG 10653 8761 60.3 768   562 TGG TAA CAT CCT AGA A  4901 AJ_P8 85653 H12 AJ_768 /5AmMC6/CCC AAG ACC TTG 10658 8795 61.7 769   563 ACT GGA GAA ACG GTA A  6462 AJ_P9 85653 A01 AJ_769 /5AmMC6/CCC AAG CTC ACT 10653 8672 60.6 770   565 ACC ATT GTC ATT GGA A  4903 AJ_P9 85653 A02 AJ_770 /5AmMC6/CCC AAT CCG TTA 10653 8770 60.6 771   566 CGT GAA GGG TAA ACA A  4904 AJ_P9 85653 A03 AJ_771 /5AmMC6/CCC AAT ACA GAC 10653 8699 60.1 772   567 TGC ACA CTC AGG TAA A  4905 AJ_P9 85653 A04 AJ_772 /5AmMC6/CCC AAT TTA CGT 10653 8696 59.3 773   568 AGT CCA ACT TGC GAA A  4906 AJ_P9 85653 A05 AJ_773 /5AmMC6/CCC AAG ACC TTA 10653 8690 59.4 774   569 CTA CCT GAA GCA GTA A  4907 AJ_P9 85653 A06 AJ_774 /5AmMC6/CCC AAC ATT GTT 10653 8687 59.4 775   570 TCT CTG ACA AGC TGA A  4908 AJ_P9 85653 A07 AJ_775 /5AmMC6/CCC AAC AGC AGT 10653 8739 61 776   571 TTA GCC AAG AAG TCA A  4909 AJ_P9 85653 A08 AJ_776 /5AmMC6/CCC AAG ACC TTG 10653 8657 60.9 777   572 GAC TCT CTC TAA CGA A  4910 AJ_P9 85653 A09 AJ_777 /5AmMC6/CCC AAG TAC TTT 10653 8672 60.1 778   573 CTT CCA GTC AGA GCA A  4911 AJ_P9 85653 A10 AJ_778 /5AmMC6/CCC AAT CAG ACA 10653 8681 60.7 779   574 ACC TTG TTC ATC GGA A  4912 AJ_P9 85653 A11 AJ_779 /5AmMC6/CCC AAT CAC CTG 10653 8712 60.7 780   575 TTG CAT TCA TAG GGA A  4913 AJ_P9 85653 A12 AJ_780 /5AmMC6/CCC AAT TTG CAG 10653 8714 59.8 781   576 TGA ACA CCA ACA GTA A  4914 AJ_P9 85653 B01 AJ_781 /5AmMC6/CCC AAG TCT GCA 10653 8699 60.4 782   577 GTA ACA CAC CAA GTA A  4915 AJ_P9 85653 B02 AJ_782 /5AmMC6/CCC AAT GTC TCA 10653 8672 59.7 783   578 GTC TCC ACA TTA GGA A  4916 AJ_P9 85653 B03 AJ_783 /5AmMC6/CCC AAG TAC ACC 10653 8672 61.2 784   579 ATT TCG CAT TTC GGA A  4917 AJ_P9 85653 B04 AJ_784 /5AmMC6/CCC AAG CTA CCA 10653 8730 60 785   580 CTT TAG AAG TAG GCA A  4918 AJ_P9 85653 B05 AJ_785 /5AmMC6/CCC AAT CAC AAG 10653 8739 60 786   581 GTT ACC ACA GGA GTA A  4919 AJ_P9 85653 B06 AJ_786 /5AmMC6/CCC AAC ACC ATG 10653 8715 61.9 787   582 GAC ACT TCT AAG GGA A  4920 AJ_P9 85653 B07 AJ_787 /5AmMC6/CCC AAC CTG AAA 10653 8736 59.3 788   583 GAG TTT CTT GCG TAA A  4921 AJ_P9 85653 B08 AJ_788 /5AmMC6/CCC AAG AGA CGT 10653 8706 61.3 789   584 GTC ATC TCA TCC AGA A  4922 AJ_P9 85653 B09 AJ_789 /5AmMC6/CCC AAT AGC GTA 10653 8723 59.2 790   585 GAC AAC TTC AAA GCA A  4923 AJ_P9 85653 B10 AJ_790 /5AmMC6/CCC AAA GTT CTC 10653 8687 58.6 791   586 TCG TTC ATA GCT GAA A  4924 AJ_P9 85653 B11 AJ_791 /5AmMC6/CCC AAA TTG GTC 10653 8736 59.7 792   587 TTC TGC ATA AAG CGA A  4925 AJ_P9 85653 B12 AJ_792 /5AmMC6/CCC AAT CGA AGG 10653 8761 58.8 793   588 AGT AGT CTA CCT GTA A  4926 AJ_P9 85653 C01 AJ_793 /5AmMC6/CCC AAT CAG GAC 10653 8715 61.8 794   589 TAC GGA AAG TTC CCA A  4927 AJ_P9 85653 C02 AJ_794 /5AmMC6/CCC AAC CGT AAC 10653 8675 62 795   590 ATC CAT GAG ACG TCA A  4928 AJ_P9 85653 C03 AJ_795 /5AmMC6/CCC AAT GCG AAA 10653 8770 60.8 796   591 GAG GTA CCG TTT ACA A  4929 AJ_P9 85653 C04 AJ_796 /5AmMC6/CCC AAG ACA CAT 10653 8675 62.1 797   592 CCA ACT GGT GAC TCA A  4930 AJ_P9 85653 C05 AJ_797 /5AmMC6/CCC AAG ACC ATC 10653 8675 61.7 798   593 CTT CAA GAG ACG TCA A  4931 AJ_P9 85653 C06 AJ_798 /5AmMC6/CCC AAG CTC TCA 10653 8690 60.6 799   594 AGT CTA AAC AGT GCA A  4932 AJ_P9 85653 C07 AJ_799 /5AmMC6/CCC AAC AAA GTA 10653 8763 58.6 800   595 GAA ACT CGT AGC TGA A  4933 AJ_P9 85653 C08 AJ_800 /5AmMC6/CCC AAC CAG AGT 10653 8795 61.3 801   596 GTG AAC ACT AGG GTA A  4934 AJ_P9 85653 C09 AJ_801 /5AmMC6/CCC AAC CTC ATG 10653 8715 61.5 802   597 AAG ACT CCA AGG GTA A  4935 AJ_P9 85653 C10 AJ_802 /5AmMC6/CCC AAA CCT GTG 10653 8666 62.1 803   598 GAC ACT ACA CCT TGA A  4936 AJ_P9 85653 C11 AJ_803 /5AmMC6/CCC AAA GTT CAG 10653 8672 59.9 804   599 AGT TCT CTC CAC TGA A  4937 AJ_P9 85653 C12 AJ_804 /5AmMC6/CCC AAG CTA CTT 10653 8721 60.4 805   600 TCA ACT GAC AGT GGA A  4938 AJ_P9 85653 D01 AJ_805 /5AmMC6/CCC AAG CCA TCT 10653 8681 60.1 806   601 TCT ACT GAA CGG TAA A  4939 AJ_P9 85653 D02 AJ_806 /5AmMC6/CCC AAT GTT TCA 10653 8687 59.4 807   602 GTC CAT TGA ACG CTA A  4940 AJ_P9 85653 D03 AJ_807 /5AmMC6/CCC AAA TTG CTT 10653 8687 59.1 808   603 CTC ACG TCA TTA GGA A  4941 AJ_P9 85653 D04 AJ_808 /5AmMC6/CCC AAT GGG AAC 10653 8739 60.8 809   604 TCT GAA ACA TCC GAA A  4942 AJ_P9 85653 D05 AJ_809 /5AmMC6/CCC AAT CGT AGA 10653 8723 58.4 810   605 GTC AAA CCA CAA GTA A  4943 AJ_P9 85653 D06 AJ_810 /5AmMC6/CCC AAC AGG TGT 10653 8786 62.5 811   606 CGT GTG AAA CAG TCA A  4944 AJ_P9 85653 D07 AJ_811 /5AmMC6/CCC AAG GTC ATT 10653 8657 62 812   607 AAG CCT TCG ACT CCA A  4945 AJ_P9 85653 D08 AJ_812 /5AmMC6/CCC AAC TTG AAG 10653 8779 61.3 813   608 TGA AGG CAA CCA TGA A  4946 AJ_P9 85653 D09 AJ_813 /5AmMC6/CCC AAC AAC TAG 10653 8761 60.1 814   609 GAG TGC TCT GGT TAA A  4947 AJ_P9 85653 D10 AJ_814 /5AmMC6/CCC AAG ACC ATA 10653 8675 61.9 815   610 GCA TCC AAG TCG TCA A  4948 AJ_P9 85653 D11 AJ_815 /5AmMC6/CCC AAT CGA GAA 10653 8723 58.4 816   611 ACA CCT GTA CAA GTA A  4949 AJ_P9 85653 D12 AJ_816 /5AmMC6/CCC AAC AGT CTT 10653 8754 58.3 817   612 TAA GCA GAA GGA CTA A  4950 AJ_P9 85653 E01 AJ_817 /5AmMC6/CCC AAC GTC AAC 10653 8699 59.8 818   613 TAC ACA GAA GGT CTA A  4951 AJ_P9 85653 E02 AJ_818 /5AmMC6/CCC AAG TCG ACA 10653 8730 60 819   614 ACA GCA TTA GGT CTA A  4952 AJ_P9 85653 E03 AJ_819 /5AmMC6/CCC AAT TGG TCA 10653 8687 59.9 820   615 GAA CTT TCC TTG CAA A  4953 AJ_P9 85653 E04 AJ_820 /5AmMC6/CCC AAC CTA GGT 10653 8752 60.5 821   616 CAA GTT TAG GTT GCA A  4954 AJ_P9 85653 E05 AJ_821 /5AmMC6/CCC AAG TCA TCT 10653 8666 61.6 822   617 GCA TCC ACA CTA GGA A  4955 AJ_P9 85653 E06 AJ_822 /5AmMC6/CCC AAA TCG CTT 10653 8690 61 823   618 GAA CCA TAC CAT GGA A  4956 AJ_P9 85653 E07 AJ_823 /5AmMC6/CCC AAA TCT GAA 10653 8763 58.8 824   619 CTG AGG AAC AAG CTA A  4957 AJ_P9 85653 E08 AJ_824 /5AmMC6/CCC AAC GTG AGC 10653 8770 61.2 825   620 ATC AGG AAC ATT TGA A  4958 AJ_P9 85653 E09 AJ_825 /5AmMC6/CCC AAT CCC TAG 10653 8697 61.2 826   621 TTC CAG TCA TGA GGA A  4959 AJ_P9 85653 E10 AJ_826 /5AmMC6/CCC AAC TCC TAG 10653 8657 60.7 827   622 TCC TGT AGT CCA GAA A  4960 AJ_P9 85653 E11 AJ_827 /5AmMC6/CCC AAG AGT CAA 10653 8699 60.2 828   623 CTC CAT GAA AGC CTA A  4961 AJ_P9 85653 E12 AJ_828 /5AmMC6/CCC AAG GTA GTC 10653 8755 61 829   624 TCA GAG AAC ACC TGA A  4962 AJ_P9 85653 F01 AJ_829 /5AmMC6/CCC AAG CTG TAG 10653 8779 59.8 830   625 GAC ATA AGA ACC GTA A  4963 AJ_P9 85653 F02 AJ_830 /5AmMC6/CCC AAG TCC AAC 10653 8739 60.4 831   626 TGA AAC AGA GCT GTA A  4964 AJ_P9 85653 F03 AJ_831 /5AmMC6/CCC AAG TGC AAC 10653 8795 62.1 832   627 TAC AGG ACA GTG TGA A  4965 AJ_P9 85653 F04 AJ_832 /5AmMC6/CCC AAT GAA ACA 10653 8763 59.3 833   628 GAC AAG TAG CGT TCA A  4966 AJ_P9 85653 F05 AJ_833 /5AmMC6/CCC AAA AAC TGT 10653 8696 59.5 834   629 AGC TTT CCC TTG GAA A  4967 AJ_P9 85653 F06 AJ_834 /5AmMC6/CCC AAT CCG TAG 10653 8761 60 835   630 AGC AGT GAG TTT ACA A  4968 AJ_P9 85653 F07 AJ_835 /5AmMC6/CCC AAG GTT CAT 10653 8672 60.6 836   631 GCA TCC TCT TCA AGA A  4969 AJ_P9 85653 F08 AJ_836 /5AmMC6/CCC AAA CCT TTG 10653 8761 61.3 837   632 TGG AGT CAA GCA TGA A  4970 AJ_P9 85653 F09 AJ_837 /5AmMC6/CCC AAA CCT TTG 10653 8736 59.7 838   633 TGA GCA GAG CAT TTA A  4971 AJ_P9 85653 F10 AJ_838 /5AmMC6/CCC AAA CTG TTT 10653 8672 60.5 839   634 CCC TTA GAG CAG TCA A  4972 AJ_P9 85653 F11 AJ_839 /5AmMC6/CCC AAG CTG TAG 10653 8752 59.4 840   635 GAG TTA CAT CTC TGA A  4973 AJ_P9 85653 F12 AJ_840 /5AmMC6/CCC AAG TGG ACA 10653 8706 61.3 841   636 CTC CAG AAC TCT GTA A  4974 AJ_P9 85653 G01 AJ_841 /5AmMC6/CCC AAC GTC ATC 10653 8699 59.8 842   637 TGA CAG AAC AGA CTA A  4975 AJ_P9 85653 G02 AJ_842 /5AmMC6/CCC AAG TCC AAC 10653 8699 60.8 843   638 GAA GCA TGA CAC TTA A  4976 AJ_P9 85653 G03 AJ_843 /5AmMC6/CCC AAA GCC TAA 10653 8721 61.2 844   639 AGC CTT TGG GTT ACA A  4977 AJ_P9 85653 G04 AJ_844 /5AmMC6/CCC AAC CGT TCA 10653 8699 60.4 845   640 AAC GAC TAA GAG TCA A  4978 AJ_P9 85653 G05 AJ_845 /5AmMC6/CCC AAT CGG AAC 10653 8672 61.5 846   641 ACC TTT GGT TTC CAA A  4979 AJ_P9 85653 G06 AJ_846 /5AmMC6/CCC AAT GAC CAT 10653 8687 60 847   642 CAT GTT TGG CTT CAA A  4980 AJ_P9 85653 G07 AJ_847 /5AmMC6/CCC AAG ACC ATG 10653 8672 60.5 848   643 AGC TCT CTT GTT CAA A  4981 AJ_P9 85653 G08 AJ_848 /5AmMC6/CCC AAC TAG GTG 10653 8755 61.9 849   644 AAG TGA CAG CAT CCA A  4982 AJ_P9 85653 G09 AJ_849 /5AmMC6/CCC AAC AAG TTA 10653 8779 60.4 850   645 GGA GAC TGA CTG CAA A  4983 AJ_P9 85653 G10 AJ_850 /5AmMC6/CCC AAT CAG CAC 10653 8714 58.6 851   646 ACG AGT TCT AGT AAA A  4984 AJ_P9 85653 G11 AJ_851 /5AmMC6/CCC AAA CGT CAC 10653 8737 62.1 852   647 CTA GGT TGG GTT ACA A  4985 AJ_P9 85653 G12 AJ_852 /5AmMC6/CCC AAA CCT TGT 10653 8672 60.6 853   648 CTC TTA GCC ATG GAA A  4986 AJ_P9 85653 H01 AJ_853 /5AmMC6/CCC AAA CCT TGT 10653 8712 60.6 854   649 TAC TGT GCT AGA GCA A  4987 AJ_P9 85653 H02 AJ_854 /5AmMC6/CCC AAA CAG AGT 10653 8681 60.8 855   650 GCT TCC AAC TTC TGA A  4988 AJ_P9 85653 H03 AJ_855 /5AmMC6/CCC AAT CGT TCA 10653 8761 60.2 856   651 CGA AGT AGG GTT ACA A  4989 AJ_P9 85653 H04 AJ_856 /5AmMC6/CCC AAA AAC ATG 10653 8705 60.1 857   652 TTC CGT AGT TGC CAA A  4990 AJ_P9 85653 H05 AJ_857 /5AmMC6/CCC AAT GAC CAC 10653 8699 60.9 858   653 AAC ATA GCA TGT CGA A  4991 AJ_P9 85653 H06 AJ_858 /5AmMC6/CCC AAG CAT AAA 10653 8739 60.2 859   654 CAC TCT GGA CAG GTA A  4992 AJ_P9 85653 H07 AJ_859 /5AmMC6/CCC AAG CTA ACA 10653 8699 59.7 860   655 ACC ATC GAG AGT CTA A  4993 AJ_P9 85653 H08 AJ_860 /5AmMC6/CCC AAG TGA AAC 10653 8699 59.7 861   656 TCA CAC GAG ACT CTA A  4994 AJ_P9 85653 H09 AJ_861 /5AmMC6/CCC AAG TAA CAA 10653 8739 60.9 862   657 ACC CAT GAG CTG TGA A  4995 AJ_P9 85653 H10 AJ_862 /5AmMC6/CCC AAG TCG ACA 10653 8755 61.9 863   658 TCA CAG TCA AGG TGA A  4996 AJ_P9 85653 H11 AJ_863 /5AmMC6/CCC AAG AAC TCT 10653 8672 60.4 864   659 CTC TGC ACA TTG TGA A  4997 AJ_P9 85653 H12 AJ_864 /5AmMC6/CCC AAC TGC ACA 10653 8687 60.1 865   660 CAT GGT TTC TTT GAA A  4998 AJ_P10 85653 A01 AJ_865 /5AmMC6/CCC AAT AAA GCA 10653 8754 58.7 866   662 CTT TGA GAG TAC CGA A  4999 AJ_P10 85653 A02 AJ_866 /5AmMC6/CCC AAA TCG CTT 10653 8687 59.1 867   663 GTT TAA CCT ACT GGA A  5000 AJ_P10 85653 A03 AJ_867 /5AmMC6/CCC AAC GTT GAG 10653 8745 59 868   664 TTT AAG CTA CCA GAA A  5001 AJ_P10 85653 A04 AJ_868 /5AmMC6/CCC AAG TTT CAC 10653 8681 60 869   665 TAC ACG ACT TCG AGA A  5002 AJ_P10 85653 A05 AJ_869 /5AmMC6/CCC AAT GGA GAC 10653 8712 60.4 870   666 AGT CTT CCC TTT GAA A  5003 AJ_P10 85653 A06 AJ_870 /5AmMC6/CCC AAG TTT CAC 10653 8712 61.1 871   667 TGC ACT TCA AGG TGA A  5004 AJ_P10 85653 A07 AJ_871 /5AmMC6/CCC AAC CAG TCT 10653 8657 61.2 872   668 GGT TCT ACT ACA CGA A  5005 AJ_P10 85653 A08 AJ_872 /5AmMC6/CCC AAA TTC TCG 10653 8712 59.9 873   669 TTC TCA GAG TCA GGA A  5006 AJ_P10 85653 A09 AJ_873 /5AmMC6/CCC AAG TTA CCA 10653 8699 60.1 874   670 ACA CCT GAG AAG CTA A  5007 AJ_P10 85653 A10 AJ_874 /5AmMC6/CCC AAA CTA CTG 10653 8779 60.1 875   671 TCA AAG GAG TAG GCA A  5008 AJ_P10 85653 A11 AJ_875 /5AmMC6/CCC AAG TTC CCA 10653 8675 62 876   672 AGA CCT ACA AGC TGA A  5009 AJ_P10 85653 A12 AJ_876 /5AmMC6/CCC AAT TTA GCC 10653 8714 59 877   673 TAA CAG CAA CAG GTA A  5010 AJ_P10 85653 B01 AJ_877 /5AmMC6/CCC AAA TCT GTT 10653 8687 59 878   674 CTC TGC AAA GTC GTA A  5011 AJ_P10 85653 B02 AJ_878 /5AmMC6/CCC AAA GTC CTT 10653 8681 60.3 879   675 GTC TCA AAC TCA GGA A  5012 AJ_P10 85653 B03 AJ_879 /5AmMC6/CCC AAA TCT TGT 10653 8736 59.3 880   676 GTG TCG AAG CAA CTA A  5013 AJ_P10 85653 B04 AJ_880 /5AmMC6/CCC AAG TGC AAC 10653 8770 60.4 881   677 TGG AGA CAG ACT TTA A  5014 AJ_P10 85653 B05 AJ_881 /5AmMC6/CCC AAA CTG TCT 10653 8696 59.3 882   678 TGT TCG AAC AGC ATA A  5015 AJ_P10 85653 B06 AJ_882 /5AmMC6/CCC AAT TTG TAC 10653 8687 59.4 883   679 ATC GCT TCA TCG GAA A  5016 AJ_P10 85653 B07 AJ_883 /5AmMC6/CCC AAT ACA GAA 10653 8739 58.9 884   680 GGA GTA CCT GAC CTA A  5017 AJ_P10 85653 B08 AJ_884 /5AmMC6/CCC AAT CGC AAA 10653 8714 59.4 885   681 GAA GTA CCA GTT TCA A  5018 AJ_P10 85653 B09 AJ_885 /5AmMC6/CCC AAC TGG TAG 10653 8779 60.4 886   682 ACA TGC ATA GAA GCA A  5019 AJ_P10 85653 B10 AJ_886 /5AmMC6/CCC AAG AGA ACT 10653 8795 62.2 887   683 ACC GTT GTG AAG GCA A  5020 AJ_P10 85653 B11 AJ_887 /5AmMC6/CCC AAT TTC GAG 10653 8714 58.8 888   684 AGT CAC ATC AAC AGA A  5021 AJ_P10 85653 B12 AJ_888 /5AmMC6/CCC AAC GGT AAG 10653 8712 60.1 889   685 GCT ACC TCT TTG TAA A  5022 AJ_P10 85653 C01 AJ_889 /5AmMC6/CCC AAC TAC GCT 10653 8723 58.5 890   686 ACT AAA GTA AAG GCA A  5023 AJ_P10 85653 C02 AJ_890 /5AmMC6/CCC AAC GTG AGT 10653 8721 60 891   687 TCG TTA ACT ACC AGA A  5024 AJ_P10 85653 C03 AJ_891 /5AmMC6/CCC AAT GGT CTA 10653 8681 60.2 892   688 GCA TTC AAC TAC CGA A  5025 AJ_P10 85653 C04 AJ_892 /5AmMC6/CCC AAT GTT TCA 10653 8672 60 893   689 GAC CTG ACT ACC TGA A  5026 AJ_P10 85653 C05 AJ_893 /5AmMC6/CCC AAT AAC AGA 10657 8699 60.3 894   690 ACC CAT GCT CAG GTA A  7190 AJ_P10 85653 C06 AJ_894 /5AmMC6/CCC AAA CAC GTT 10653 8687 60 895   691 GCA CTT TAC TTT GGA A  5028 AJ_P10 85653 C07 AJ_895 /5AmMC6/CCC AAT GCT GAC 10653 8723 59.3 896   692 GTA CAC AAA CAA GTA A  5029 AJ_P10 85653 C08 AJ_896 /5AmMC6/CCC AAA GCT GTT 10653 8736 59.9 897   693 GCT GTT AAA CCG TAA A  5030 AJ_P10 85653 C09 AJ_897 /5AmMC6/CCC AAC ATG TTG 10653 8761 60.8 898   694 TGG TAG CTA CCG AAA A  5031 AJ_P10 85653 C10 AJ_898 /5AmMC6/CCC AAA TCT CTG 10653 8761 60.2 899   695 TGG TAG CAT AAC GGA A  5032 AJ_P10 85653 C11 AJ_899 /5AmMC6/CCC AAG AGC TCT 10653 8736 57.8 900   696 CGT GTT ACT AAA GTA A  5033 AJ_P10 85653 C12 AJ_900 /5AmMC6/CCC AAA GCC TTG 10653 8727 59.5 901   697 GTT GTC AGT CTT AAA A  5034 AJ_P10 85653 D01 AJ_901 /5AmMC6/CCC AAG TAC CTC 10653 8657 60.2 902   698 TAC TCT GAC TCA GGA A  5035 AJ_P10 85653 D02 AJ_902 /5AmMC6/CCC AAG GCA TAC 10653 8666 61.9 903   699 AAC TCT GAC CTG TCA A  5036 AJ_P10 85653 D03 AJ_903 /5AmMC6/CCC AAC CAG TAA 10653 8675 62.6 904   700 ACC AGT GAC TTG CCA A  5037 AJ_P10 85653 D04 AJ_904 /5AmMC6/CCC AAG ACT CCT 10653 8721 60.6 905   701 TGG TTC AAC GGT AAA A  5038 AJ_P10 85653 D05 AJ_905 /5AmMC6/CCC AAC TTA GGT 10653 8770 59.7 906   702 AGG TAG CAC ACT GAA A  5039 AJ_P10 85653 D06 AJ_906 /5AmMC6/CCC AAA GTC CAG 10653 8714 58.8 907   703 AGC ACA TTT CAT AGA A  5040 AJ_P10 85653 D07 AJ_907 /5AmMC6/CCC AAG GCT ACA 10653 8675 61.6 908   704 TGT CAC CTA ACC AGA A  5041 AJ_P10 85653 D08 AJ_908 /5AmMC6/CCC AAT GTC CAT 10653 8672 60.4 909   705 GAC TTT CCT AAC GGA A  5042 AJ_P10 85653 D09 AJ_909 /5AmMC6/CCC AAG CAC ATG 10653 8699 61.2 910   706 GTT CCA CAT AAA CGA A  5043 AJ_P10 85653 D10 AJ_910 /5AmMC6/CCC AAG CCA TGT 10653 8699 61.4 911   707 TGC ACA CTA CAA AGA A  5044 AJ_P10 85653 D11 AJ_911 /5AmMC6/CCC AAA CGC ATC 10653 8739 60.9 912   708 CAA AGT TAG GGT ACA A  5045 AJ_P10 85653 D12 AJ_912 /5AmMC6/CCC AAC CAC TCG 10653 8706 60.1 913   709 TAG TCT ACT AGG AGA A  5046 AJ_P10 85653 E01 AJ_913 /5AmMC6/CCC AAA CTG TGT 10653 8752 59.8 914   710 TGT CTC ACT AGA GGA A  5047 AJ_P10 85653 E02 AJ_914 /5AmMC6/CCC AAG TAC TCC 10653 8657 61.1 915   711 TAC TCG TAC ATG GCA A  5048 AJ_P10 85653 E03 AJ_915 /5AmMC6/CCC AAT AAC ACG 10653 8714 59.9 916   712 AAA GCT TGT GCA TCA A  5049 AJ_P10 85653 E04 AJ_916 /5AmMC6/CCC AAT TTC TAG 10653 8687 59.6 917   713 AAC TGT GCT TGC ACA A  5050 AJ_P10 85653 E05 AJ_917 /5AmMC6/CCC AAG GTG TAC 10653 8777 61.7 918  714 CTT TGA CCA GTG AGA A  5051 AJ_P10 85653 E06 AJ_918 /5AmMC6/CCC AAG TTA CCT 10653 8681 60.1 919   715 CTT GCC ATA CGA GAA A  5052 AJ_P10 85653 E07 AJ_919 /5AmMC6/CCC AAG AAC GTT 10653 8714 59.6 920   716 CTG CTC ATA GCA AAA A  5053 AJ_P10 85653 E08 AJ_920 /5AmMC6/CCC AAA CGC TTC 10653 8696 59.4 921   717 TTC ATT GTA ACA GGA A  5054 AJ_P10 85653 E09 AJ_921 /5AmMC6/CCC AAG AGT CTC 10653 8657 59.8 922   718 GAC TCC TCT ACT AGA A  5055 AJ_P10 85653 E10 AJ_922 /5AmMC6/CCC AAG AGT ACA 10653 8690 59.8 923   719 GAA CCT CAC TTT CGA A  5056 AJ_P10 85653 E11 AJ_923 /5AmMC6/CCC AAG TAC TGC 10653 8699 60.3 924   720 TGA CAC AAC TAA CGA A  5057 AJ_P10 85653 E12 AJ_924 /5AmMC6/CCC AAA GCC TTT 10653 8761 60.1 925   721 GGT AGT CAG ACA GTA A  5058 AJ_P10 85653 F01 AJ_925 /5AmMC6/CCC AAA GGC TAC 10653 8714 59 926   722 TCA GAA CAA CTT TGA A  5059 AJ_P10 85653 F02 AJ_926 /5AmMC6/CCC AAG TAC CTC 10653 8675 61.6 927   723 ACT CAA GCA TCA GGA A  5060 AJ_P10 85653 F03 AJ_927 /5AmMC6/CCC AAA TAG TCT 10653 8752 60.3 928   724 CAG TGT GCT AGT GCA A  5061 AJ_P10 85653 F04 AJ_928 /5AmMC6/CCC AAG TCC ACT 10653 8697 62 929   725 TTC TGC ACT AAG GGA A  5062 AJ_P10 85653 F05 AJ_929 /5AmMC6/CCC AAC AGT GCT 10653 8723 60.3 930   726 TGC AAA CAT CAA AGA A  5063 AJ_P10 85653 F06 AJ_930 /5AmMC6/CCC AAA CTT GTC 10653 8712 59.5 931   727 TCT CTG AGT ACA GGA A  5064 AJ_P10 85653 F07 AJ_931 /5AmMC6/CCC AAA GTT CTC 10653 8730 60.2 932   728 CAC AAG TGT CAG AGA A  5065 AJ_P10 85653 F08 AJ_932 /5AmMC6/CCC AAG TCT TCA 10653 8690 60.4 933   729 CAC TCA GAA CGT GAA A  5066 AJ_P10 85653 F09 AJ_933 /5AmMC6/CCC AAT CCG AAG 10653 8754 59 934   730 TTG CGT AGA CTA AAA A  5067 AJ_P10 85653 F10 AJ_934 /5AmMC6/CCC AAG AAA CAT 10653 8699 60.1 935   731 CGT ACA CAG TCT CGA A  5068 AJ_P10 85653 F11 AJ_935 /5AmMC6/CCC AAG AAC CAT 10653 8675 62.4 936   732 CAC CTG TCA GCA TGA A  5069 AJ_P10 85653 F12 AJ_936 /5AmMC6/CCC AAC GAC ATA 10653 8739 60.5 937   733 CCT AAA GCA TGG TGA A  5070 AJ_P10 85653 G01 AJ_937 /5AmMC6/CCC AAG GTC ACA 10653 8666 61.9 938   734 GCA CTT TCC ACT AGA A  5071 AJ_P10 85653 G02 AJ_938 /5AmMC6/CCC AAC GAG TTA 10653 8705 59.6 939   735 CAC GTT TGC CTA AAA A  5072 AJ_P10 85653 G03 AJ_939 /5AmMC6/CCC AAG TAC GCT 10653 8681 58.9 940   736 AGT CTC TCA CAT AGA A  5073 AJ_P10 85653 G04 AJ_940 /5AmMC6/CCC AAA GTG TCT 10653 8681 59.9 941   737 GAC CAT ACT TAC CGA A  5074 AJ_P10 85653 G05 AJ_941 /5AmMC6/CCC AAC GTT CCA 10653 8699 60 942   738 TAC CAA GGA CAT AGA A  5075 AJ_P10 85653 G06 AJ_942 /5AmMC6/CCC AAG GAC TTC 10653 8681 59.1 943   739 GAC TTC CTA CTA AGA A  5076 AJ_P10 85653 G07 AJ_943 /5AmMC6/CCC AAT GAC GTT 10653 8681 60.5 944   740 GTA AAC CTC TCA CGA A  5077 AJ_P10 85653 G08 AJ_944 /5AmMC6/CCC AAG CAC TGT 10653 8690 61 945   741 GTA AAC AAC CTT CGA A  5078 AJ_P10 85653 G09 AJ_945 /5AmMC6/CCC AAC ATG TAG 10653 8763 58.1 946   742 AGA AAC TCT CGA GAA A  5079 AJ_P10 85653 G10 AJ_946 /5AmMC6/CCC AAC AGC TTC 10653 8672 59.5 947   743 CTC ATA GTC TTA GGA A  5080 AJ_P10 85653 G11 AJ_947 /5AmMC6/CCC AAG TCC TAC 10653 8675 61.3 948   744 ACA CAG TCA TAC GGA A  5081 AJ_P10 85653 G12 AJ_948 /5AmMC6/CCC AAG TCC ATA 10653 8666 62.3 949   745 CAT CCG AAC TGT GCA A  5082 AJ_P10 85653 H01 AJ_949 /5AmMC6/CCC AAG AAC TTC 10653 8681 61 950   746 CAC TTA GCA TGT GCA A  5083 AJ_P10 85653 H02 AJ_950 /5AmMC6/CCC AAG GTT CTA 10653 8690 60.7 951   747 CAT CAC GTA CGC AAA A  5084 AJ_P10 85653 H03 AJ_951 /5AmMC6/CCC AAG AGT GCT 10653 8730 60 952   748 ACC TTC GTA CAG AAA A  5085 AJ_P10 85653 H04 AJ_952 /5AmMC6/CCC AAA TAA GTC 10653 8763 58.8 953   749 CTG AAG GAA CGC ATA A  5086 AJ_P10 85653 H05 AJ_953 /5AmMC6/CCC AAG TGC AAC 10653 8739 61.4 954   750 GAG ACC TTT GAC AAA A  5087 AJ_P10 85653 H06 AJ_954 /5AmMC6/CCC AAG CAC TGT 10653 8681 61.5 955   751 TGA AAC CCT TTC GAA A  5088 AJ_P10 85653 H07 AJ_955 /5AmMC6/CCC AAA CTC GTC 10653 8681 61 956   752 ACC TTT GGG TAA ACA A  5089 AJ_P10 85653 H08 AJ_956 /5AmMC6/CCC AAA GCC TTC 10653 8721 60.2 957   753 TTG GTC ATA GAC AGA A  5090 AJ_P10 85653 H09 AJ_957 /5AmMC6/CCC AAC AAC GGT 10653 8752 61.1 958   754 ACT TTG TTG GTA GCA A  5091 AJ_P10 85653 H10 AJ_958 /5AmMC6/CCC AAC ATT CTG 10653 8752 60.6 959   755 GTG TTA CGA ACT GGA A  5092 AJ_P10 85653 H11 AJ_959 /5AmMC6/CCC AAT GAA ACC 10653 8699 61 960   756 ATC CAT GTC AGA GCA A  5093 AJ_P10 85653 H12 AJ_960 /5AmMC6/CCC AAA ACT GAC 10653 8761 61.9 961   757 CAT TGT GGT GTG CAA A  5094

Example 11—Titration or Dilution Series

The ability to perform multiple experiments in parallel enables straightforward exploration of the counting results from samples with a range of starting concentrations or amounts of target, sometimes known as a titration experiment or a dilution series.

An example of dilution series data for a labeled RPLPO gene sequence is shown in FIG. 26. Plotted in the figure is the counting result N for each array where the nominal starting concentration of mRNA in the reaction is shown on the X axis.

Some of the graphical output from the analysis software for the same experiment is shown in FIG. 27. For each array, there is a compound display with the following elements: (i) an intensity histogram (green) for the index spots, (ii) a blue line registered with the histogram, showing the dynamic threshold for spot counting, (iii) a 32×32 grid which is a digital representation of each array. A white site in the grid denotes a spot whose intensity was above the dynamic threshold, and a black site denotes that the intensity was below the dynamic threshold, and (iv) the result N and the quality score Q is reported for each array as text.

While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments may be provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. 

1.-20. (canceled)
 21. A method for determining the number of a target molecule on an array, comprising: (a) acquiring image data of a region of an array, wherein the array comprises a plurality of stochastically labeled and non-labeled features, and wherein the features comprise oligonucleotide probes; (b) measuring a signal intensity and a local background intensity for one of the plurality of stochastically labeled and non-labeled features based on the acquired image data; (c) calculating a local background corrected signal intensity for the one of the plurality of stochastically labeled and non-labeled features using the signal intensity and the local background intensity measured in (b); (d) transforming the local background corrected signal intensity calculated in (c) for the one of the plurality of stochastically labeled and non-labeled features to determine the number of stochastically labeled and non-labeled features in the of the array; and (e) calculating the number of a target molecule based on the number of stochastically labeled and non-labeled features determined in (d) within the region of the array.
 22. The method of claim 21, wherein acquiring the image data of the region of the array comprises acquiring the image data of the region of the array from an optical imaging system, wherein the optical imaging system is a fluorescence imaging system or a phosphorescence imaging system, and wherein the optical imaging system operates in a transmitted light, reflected light, or scattered light imaging mode, or any combination thereof.
 23. The method of claim 21, wherein the oligonucleotide probes comprises a fluorescein dye, a Cy3 dye, a Cy5 dye, or a phycoerythrin fluorophore.
 24. The method of claim 21, further comprising illuminating the region of the array using an illumination system prior to (a) acquiring the image data of the region of the array.
 25. The method of claim 21, wherein acquiring the image data of the region of the array comprises automatically locating one or more of the plurality of stochastically labeled and non-labeled features of the array.
 26. The method of claim 21, further comprising analyzing the local background corrected signal intensities for the plurality of stochastically labeled and non-labeled features to determine a dynamic signal intensity threshold for distinguishing the stochastically labeled and non-labeled features of the array.
 27. The method of claim 26, wherein determining the dynamic signal intensity threshold for distinguishing the stochastically labeled and non-labeled features of the array comprises performing, a k-means clustering analysis, a k-medoids clustering analysis, a mixture model statistical analysis, an empirical analysis based on sorting of the background corrected signal intensity values for the plurality of stochastically labeled and non-labeled features, or an empirical analysis based on sorting of pairwise differences in background corrected signal intensity values for the plurality of stochastically labeled and non-labeled features to determine a dynamic signal intensity threshold for distinguishing the plurality of stochastically labeled and non-labeled features of the array.
 28. The method of claim 26, wherein determining the dynamic signal intensity threshold for distinguishing the stochastically labeled and non-labeled features of the array comprises maximizing a quality metric relating to a statistical difference between feature intensities above the dynamic signal intensity threshold and feature intensities below the dynamic signal intensity threshold.
 29. The method of claim 26, wherein calculating the local background corrected signal intensity for the one of the plurality of stochastically labeled and non-labeled features using the signal intensity and the local background intensity measured in (b) comprises: (i) centering a predefined analysis window on an array feature within an image, (ii) calculating an intensity value statistic for signal and background pixels according to a predefined pattern of pixels within the array feature, and (iii) utilizing the intensity value statistic for signal and background pixels to calculate the local background corrected signal intensity for the array feature.
 30. The method of claim 21, wherein the intensity value statistic used for calculating the background corrected signal intensity for each of the plurality of stochastically labeled and non-labeled features is the mean, the median, or the ratio of signal to background intensities.
 31. The method of claim 21, wherein calculating the number of the target molecule based on the number of stochastically labeled and non-labeled features determined in (d) within the region of the array comprises calculating the number of the target molecule based on the number of stochastically labeled features, the number of non-labeled features within the region of the array, and the predictions of the Poisson distribution.
 32. The method of claim 21, further comprising calculating a confidence interval for the calculated number of the target molecule.
 33. A method for performing local background correction of array signal intensity data, comprising: (a) centering a predefined data analysis window on a feature within a digital image of an array; (b) calculating an intensity value statistic for signal and background pixels based on a predefined pattern of pixels within or around the feature; and (c) utilizing the intensity value statistic for signal and background pixels to calculate a background corrected signal intensity for the feature.
 34. The method of claim 33, further comprising automatically locating the feature within the array using a predefined set of fiducial features on the array.
 35. The method of claim 33, wherein the intensity value statistic used for calculation of the background corrected signal intensity for the feature is the mean, the median, or the ratio of signal to background intensities.
 36. The method of claim 33, wherein calculating the intensity value statistic for signal and background pixels comprises subtracting the mean or median background intensity from the mean or median signal intensity to determine a background corrected signal intensity value for each array feature.
 37. The method of claim 33, wherein the feature within the digital image of an array is stochastically labeled.
 38. A method for determining a dynamic image intensity threshold for use in discriminating between labeled and non-labeled features on an array comprising a plurality of labeled and non-labeled features, comprising: (a) measuring image intensity data for each of the plurality of labeled and non-labeled features of the array; (b) performing a local background correction on the measured image intensity data for each of the plurality of labeled and non-labeled features on the array to obtain local background corrected image intensity data; and (c) performing one or more statistical analyses of the local background corrected image intensity data for the plurality of labeled and non-labeled features, thereby determining a dynamic image intensity threshold for discrimination between the labeled and non-labeled features.
 39. The method of claim 38, wherein the one or more statistical analyses comprises k-means clustering, k-medoids clustering, mixture model statistical analysis, probe reference distribution methods, or an empirical analysis.
 40. The method of claim 38, wherein the plurality of labeled and non-labeled features comprises a plurality of stochastically labeled and non-labeled features. 